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Systematic Review of the Methodological Quality of Controlled Trials Evaluating Chinese Herbal Medicine in
Patients with Rheumatoid Arthritis
Journal: BMJ Open
Manuscript ID bmjopen-2016-013242
Article Type: Research
Date Submitted by the Author: 29-Jun-2016
Complete List of Authors: Pan, Xin; Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Department of Rheumatology Lopez-Olivo, M; The University of Texas MD Anderson Cancer Center
Song, Juhee; The University of Texas, MD Anderson Cancer Center, Department of Biostatistics Pratt, Gregory; The University of Texas, MD Anderson Cancer Center, Research Medical Library Suarez-Almazor, Maria; The University of Texas MD Anderson Cancer Center, General Internal Medicine
<b>Primary Subject Heading</b>:
Rheumatology
Secondary Subject Heading: Research methods, Complementary medicine, Evidence based practice, Medical publishing and peer review
Keywords: Chinese herbal medicine, Quality of randomized controlled trials, Traditional Chinese medicine, Systematic review, Rheumatoid arthritis
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Systematic Review of the Methodological Quality of Controlled Trials Evaluating Chinese
Herbal Medicine in Patients with Rheumatoid Arthritis
Xin Pan1, Maria A. Lopez-Olivo
2, Juhee Song
3, Gregory Pratt
4, Maria E. Suarez-Almazor
2.
1Department of Rheumatology, Shuguang Hospital, Shanghai University of Traditional Chinese
Medicine, Shanghai, China; 2Department of General Internal Medicine, Rheumatology Section,
3Department of Biostatistics, and
4Research Medical Library, The University of Texas MD
Anderson Cancer Center, Houston, TX 77030, USA.
Corresponding Author: Maria E. Suarez-Almazor, MD, PhD, Department of General Internal
Medicine, Unit 1467, The University of Texas MD Anderson Cancer Center, 1515 Holcombe
Boulevard, Houston, TX 77030, USA. Phone: 713-563-6209. Fax: 713-563-4491. Email:
msalmazor@mdanderson.org.
The Corresponding Author has the right to grant on behalf of all authors and does grant on
behalf of all authors a worldwide licence to the Publishers and its licensees in perpetuity, in all
forms, formats, and media (whether known now or created in the future), to i) publish,
reproduce, distribute, display, and store the Contribution; ii) translate the Contribution into
other languages, create adaptations, create reprints, include the Contribution within collections,
and create summaries, extracts, or abstracts of the Contribution; iii) create any other derivative
work(s) based on the Contribution; iv) exploit all subsidiary rights in the Contribution; v)
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include electronic links from the Contribution in third party material wherever it may be located;
and vi) licence any third party to do any or all of the above.
Word count: 3,465
Number of figures: 1
Number of tables: 4
Number of references: 151
Number of supplementary files: 1
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ABSTRACT
Objectives: Chinese herbal medicine (CHM) is a mainstay in the treatment of rheumatoid
arthritis (RA) in China. We appraised the methodological and reporting quality of randomized
controlled clinical trials (RCTs) evaluating the efficacy and safety of CHM in patients with RA.
Design: For this systematic review, two independent reviewers selected RCTs published
between 2000 and 2015 and indexed in Medline, EMBASE, Cochrane Library, or Web of
Science evaluating the use of CHM, including herbals and decoctions (e.g., “tang”), in adult
human patients with RA. Multivariable logistic regression analysis was performed to determine
study characteristics associated with high or unclear risk of bias.
Results: Out of 2,342 unique citations, we selected 119 RCTs including 18,919 patients: 10,108
patients received CHM alone and 6,550 received 1 of 11 treatment combinations.
Discontinuation rates were not reported in 57% of the studies. A high risk of bias was observed
across all domains: 21% had a high risk for selection bias (11% from sequence generation, 30%
from allocation concealment), 85% for performance bias, 89% for detection bias, 4% for attrition
bias, and 40% for reporting bias. In multivariable analysis, fewer authors was associated with
selection bias (allocation concealment), performance bias, and attrition bias, and earlier year of
publication and funding source not reported or disclosed were associated with selection bias
(sequence generation). Studies published in non-English language were associated with reporting
bias. Poor adherence to recommended reporting standards (less than 60% of the studies not
providing sufficient information) was observed in 11 of the 23 sections evaluated.
Conclusions: Studies evaluating CHM often fail to meet expected methodological criteria, and
high-quality evidence is lacking. Future studies of CHM should be methodologically robust and
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adhere to reporting guidelines such as the Consolidated Standards of Reporting Trials statement
for CHM.
Keywords: traditional Chinese medicine, Chinese herbal medicine, rheumatoid arthritis,
randomized controlled trial, systematic review
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ARTICLE SUMMARY
1. First study appraising both methodological quality and adherence to reporting standards
specifically in RCTs evaluating Chinese herbal medicines in patients with rheumatoid
arthritis.
2. Serious methodological and reporting flaws still exist in RCTs evaluating the effects of
Chinese herbal medicines in rheumatoid arthritis. Potential for selection bias was high
across all domains evaluated and adherence to reporting standards is still a concern.
3. Earlier year of publication, fewer authors, funding not reported or disclosed, and
publication in a language other than English were the study characteristics associated
with risk of bias.
4. Our systematic review is constrained by the available resources and data.
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INTRODUCTION
Chinese herbal medicines (CHMs) have been used to treat rheumatoid arthritis (RA) for many
years, mostly in Asia. The use of CHMs is generally based on experience and is influenced by a
holistic concept of health.[1] In traditional Chinese medicine (TCM), RA belongs to the category
of “bi syndrome;” i.e., it is believed to be caused by attacks of wind, cold, dampness, or heat,
which cause disharmony between bodily systems.[2, 3] Patients are classified as having a
particular TCM syndrome according to their symptoms and then treated with CHMs to decrease
inflammation by restoring the affected system or to ameliorate the side effects of disease-
modifying antirheumatic drugs.[4] TCM guidelines have been developed by the Chinese
government for the diagnosis and treatment of these syndromes [5-7].
There are numerous CHM preparations for the treatment of RA, including decoctions,
whole plants, plant extracts, and patented formulas,[8-10] all of which can be given as a single
herb or a mixture of herbs.[11] Patented CHMs are often offered as chemical preparations,
tablets, and capsules with simple and convenient dosing schedules and reduced aftertaste.[1, 11]
This has increased the acceptance of CHM in Western countries. In 2002, a national survey
conducted in the United States reported that almost 20% of adults had used herbal therapies in
the past year.[12] In the United Kingdom, a systematic review of 89 surveys on the use of
complementary medicine showed that more than 50% of respondents with a chronic condition
reported using this type of medicine during their lifetime.[13] Furthermore, the use rate of herbal
therapies in patients with arthritis in US primary care settings has been reported to be as high as
90%.[14]
After the introduction of evidence-based medicine in China, several randomized
controlled trials (RCT) were conducted to evaluate the efficacy of CHMs for RA.[9, 11, 15, 16]
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However, the methodology used to conduct these trials was inconsistent, and the results were
conflicting. Quality of reporting is intrinsically linked to the methodological quality of RCTs.
Criteria for standardization facilitate complete and transparent reporting and help to improve
critical appraisal and interpretation of an RCT. Since the development of the Consolidated
Standards of Reporting Trials (CONSORT) statement in 1996, most high-impact journals have
endorsed its use to improve reporting of RCTs.[17] In 2006, the CONSORT extension for
reporting herbal medicines was developed, and in 2007, a draft of the extension for reporting
TCM was released.[18]
To date, no systematic review has explored the study characteristics associated with
methodological quality in controlled trials (randomized or not) evaluating the efficacy,
effectiveness, or safety of CHMs in the treatment of RA. The objectives of our study were to
appraise the methodological quality of these studies by ascertaining potential risk of bias, to
identify publication factors associated with methodological flaws, and to determine the quality of
reporting according to CONSORT recommendations.
METHODS
We report our methods and results according to the Preferred Reporting Items for Systematic
Review and Meta-Analysis statement.
Information sources
We searched electronic databases (Medline, EMBASE, Cochrane Library, and Web of Science)
from inception through June 2015 for studies evaluating the use of CHM, including herbals or
decoctions (e.g., “tang”), in patients with RA (search terms are listed in Appendix 1). Our search
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was restricted to human studies and excluded case reports but was not limited by language, year
of publication, or type of publication. We also searched the reference lists of potentially relevant
citations (controlled trials and reviews, although reviews themselves were later excluded from
the analysis) to identify additional studies that were not published or otherwise found. EndNote
X6 and DistillerSR were used to manage the records retrieved.
Study selection and eligibility criteria
Two reviewers (X.P. and Pratibha Nayak) independently screened the titles and abstracts of all
citations obtained by our searches. They resolved any disagreements through discussion and
consensus. When no consensus was reached, a third party acted as an adjudicator (M.L.-O.). We
included any RCT evaluating the efficacy, effectiveness, or safety of CHMs in adult patients (age
≥18 years) with RA. All types of CHMs were considered: (i) patented medicines (pharmaceutical
preparation or formulations) made from herbs (e.g., tablets, liquids, granules, plasters, injections,
capsules), (ii) herbal decoctions (e.g., “tang”), and (iii) plants (whole or extracts). Any type of
drug and placebo comparison and any follow-up duration were considered for inclusion. We
excluded studies that were published before the year 2000 (4 years after the publication of the
initial CONSORT statement),[17] studies published in an abstract format, studies with a non-RA
control group, studies that were a subanalysis of parent studies.
Data collection and outcome measures
One author (X.P.) extracted the data, which were then cross-checked by another author (M.L.-
O.). A standardized extraction form was used to collect information about the characteristics of
the RCTs and their participants, types of interventions, reported outcomes, and sources of
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funding. Our primary outcome measures were the methodological and reporting quality of the
RCTs.
Methodological quality in individual studies
The quality of each selected RCT was evaluated independently by two reviewers using the
Cochrane risk of bias tool [19] for RCTs published in English. RCTs published in non-English
languages were translated and evaluated by one reviewer (X.P.) and cross-checked by another
(M.L.-O.). In brief, each RCT was evaluated for its potential bias in five domains: selection,
performance, detection, attrition, and reporting. These domains specifically evaluate how the
random sequence was generated, methods of allocation concealment, blinding of participants and
personnel, blinding of the outcome assessment, how incomplete outcome data was handled, and
if there was evidence of selective outcome reporting. Each potential source of bias was graded as
low, unclear, or high, and a justification for each judgment was provided.
Quality of reporting
We examined how closely the RCTs adhered to reporting standards using the CONSORT
statement for TCM,[20] which focuses only on CHM (i.e., acupuncture, moxibustion, cupping,
and massage are not considered). It is a 23-item checklist, and the major recommendations for
transparent reporting are i) title and abstract should reflect the unique aspects of TCM, ii)
rationale of formulation selection should be described, iii) diagnostic criteria should be specified
for both TCM and conventional medicine, iv) detailed information on the treatment and control
interventions should be included, v) the outcome in TCM terms should be included, and vi) the
ethics approval number and trial registration number should be included.
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Summary measures and synthesis of results
Descriptive statistics were used to report RCT and participant characteristics, as well as the
methodological quality of the RCTs. Risk of bias assessment was summarized per domain.
Bivariate analysis was used to compare RCT characteristics according to the risk of bias
judgment. Univariate and multivariable logistic regressions were performed to determine the
factors associated with high or unclear risk of bias in the five domains in RCTs. We combined
the unclear and high risk of bias categories for the analyses. The variables tested as predictors
were year of publication, sample size, number of authors, publication language (English or non-
English), reporting or disclosing of funding (yes or no), and setting (academic or non-academic).
Variables with a univariate p value <0.15 were initially included in a multivariable logistic
regression model and reduced using the stepwise selection method. Associations were described
using odds ratios (ORs) and their associated 95% confidence intervals (CIs). We categorized
each CONSORT TCM checklist item as reported or not reported.[20, 21] We then summarized
our findings in five sections: title/abstract, introduction, methods, results, and discussion.
Subgroup analyses were performed to compare rates of potential bias (low risk or unclear/high
risk) and adherence to reporting guidelines according to (i) publication before or after the
Cochrane risk of bias tool was released and (ii) publication before or after the CONSORT
statement for TCM was released. SAS version 9.3 (SAS Institute, Inc., Cary, NC) was used to
carry out the computations for all analyses. Apart from the univariate analysis, p < 0.05 was
considered statistically significant.
RESULTS
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RCT selection
Out of 2,342 unique citations, 232 full-text articles were retrieved to assess for eligibility. Of
those, 119 RCTs were included [22-140] evaluating 18,919 patients. Figure 1 shows the number
of studies screened, assessed for eligibility, and included in the review, with reasons for
exclusion at each stage.
Characteristics of the included studies
Table 1 shows the characteristics of the included RCTs. Two-thirds of the RCTs were published
before the CONSORT statement for TCM and herbal interventions was published (2000-2007).
One RCT was conducted in the United States, one in Korea, and the rest in China. Most were
single-center studies and were not indexed in the ISI Web of Knowledge database but were
indexed in the China National Knowledge Infrastructure database (CNKI).
Outcomes reported varied across RCTs. More than half of the RCTs assessed efficacy
(e.g., disease activity score either 28 [141] or 44; [142] 20%, 30%, 50%, or 70% improvement,
according to American College of Rheumatology criteria,[143] in tender or swollen joint counts,
physician global assessment, or grip strength; or good to moderate improvement according to
European League Against Rheumatism criteria),[144] laboratory outcomes (e.g., erythrocyte
sedimentation rate, C-reactive protein, rheumatoid factor, or anti-cyclic citrullinated peptides), or
adverse events. However, less than 56% of RCTs reported on patient-reported outcomes (e.g.,
pain, patient global assessment, health assessment questionnaire, or morning stiffness), and only
3% reported radiographic outcomes (e.g., Sharp score, erosion, joint narrowing, marked
radiographic progression, or no progression). Thirty-one RCTs (26%) reported improvement of
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symptoms but did not provide additional details on the type of symptoms or how these symptoms
were assessed.
Table 1. Summary of characteristics of the randomized controlled trials (RCTs) included in our
analysis (n = 119).
RCT characteristic No. of RCTs (%)a
Duration
Less than 6 months 93 (78)
More than 6 months 23 (19)
Not reported 3 (3)
Year
2000-2007 (before CONSORT TCM)[18, 21, 145] 80 (67)
2008-2014 39 (33)
Language
English 18 (15)
Chinese 101 (85)
Country
China 117 (98)
Korea 1 (1)
United States 1 (1)
Scope
Single-center 108 (91)
Multicenter 11 (9)
Impact Factor 2013
Web of Science (score range from 0.59 to 2.711) 13 (11)
Web of Science (score range from 7.871 to 16.104) 4 (3)
Indexed in CNKI (score range from 0.031 to 1.068) 101 (85)
Not indexedb 1 (1)
Outcomesc
Disease activity score 15 (13)
ACR 20/30 28 (24)
Tender joint count 72 (61)
Swollen joint count 78 (66)
Health assessment questionnaire 19 (16)
Pain 53 (45)
Morning stiffness 66 (55)
Laboratory outcomes (ESR, CRP, RF, or anti-CCP) 91 (76)
Radiographic outcomes 3 (3)
Discontinuations 51 (43)
Adverse eventsd 76 (64)
Funding 27 (23)
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CHM preparation (main intervention)
Plant or extract (one herb) 3 (3)
Decoction alone 15 (13)
Decoction + patented 2 (2)
Individualized (not following guidelines or with
modifications)
52 (44)
Patented 43 (36)
Patented + individualized 4 (3)
Most common CHM (>1 study)
Tripterygium wilfordii/Tripterygium polyglycosides (alone
or combined)
15 (13)
JuanBi decoction/mixture or Yishen JuanBi capsule
(including those with changes or combined)
11 (9)
Feng Shi decoction/granules/wine/injection (including
those with changes or combined)
10 (8)
Total glucosides of peony 6 (5)
Xinfeng capsule 4 (3)
Zhengqing Fengtongning (alone or combined) 4 (3)
Bi Qi capsule 3 (3)
Lugua polypeptide injection 3 (3)
Guizhi Shaoyao Zhimu decoction 3 (3)
Tongbi (tablets or decoction) 3 (3)
Xiatianwu 3 (3)
Bizhongxiao 2 (2)
Sanbi decoction 2 (2)
Shi Re Bi granule/mixture 2 (2)
Siwu wuteng decoction 2 (2)
Unspecified (including decoctions without a name) 11 (9) aPercentages have been rounded.
bNot indexed in Web of Science or CNKI.
cRCTs can report on one or more outcomes.
dIncluding either clinical safety or laboratory parameters (alanine transaminase, aspartate
transaminase, creatinine, white blood cell count, platelet count, or hemoglobin).
Abbreviations: ACR 20/30 = American College of Rheumatology criteria for improvement at
20% or 30%; anti-CCP = anti-cyclic citrullinated peptide antibodies; CHM = Chinese herbal
medicine; CNKI = China National Knowledge Infrastructure database; CONSORT TCM =
Consolidated Standards of Reporting Trials statement for traditional Chinese medicine (including
herbal interventions); CRP = C-reactive protein; ESR = erythrocyte sedimentation rate; RF =
rheumatoid factor.
Characteristics of the participants and interventions
Most participants included in the RCTs met the 1987 American College of Rheumatology
diagnostic criteria for RA.[146] One RCT included only patients meeting the 2010 ACR
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classification criteria [147] and in another RCT patients included met either the 1987 or 2010
criteria. In addition, 52.5% of the participants met the criteria for one or more of the traditional
TCM “pathological factors” or syndromes (i.e., feng [wind], shi [damp], tan [phlegm], re [heat],
qi, or yin deficiency). The most common pathological factors reported are listed in Table 2. A
total of 10,108 patients received a single CHM and 6,550 received 1 of 11 treatment
combinations. Of those receiving combination treatment, 5,061 patients received combinations
that included CHMs (with disease-modifying antirheumatic drugs, nonsteroidal anti-
inflammatory drugs, steroids, or antibiotics). More than half of the CHMs were individualized
preparations targeting pain relief and improvement in joint function. In the control groups, 1,402
patients received disease-modifying antirheumatic drugs alone, (i.e., methotrexate, leflunomide,
sulfasalazine, or etanercept), 644 received nonsteroidal anti-inflammatory drugs alone, and 165
received an inert placebo. In 35 studies, patients were described as having active disease, and
two RCTs included patients with refractory disease, one included patients with early RA, three
included patients at intermediate stages of RA, and one included patients with both RA and
anemia. Discontinuation rates were not reported in 68 RCTs, but in those that reported
discontinuation rates, they ranged from 0% to 55%.
Table 2. Characteristics of the participants in the 119 randomized controlled trials included in
our analysis (n = 18,919, ranging from 30 to 3,789 patients per trial)
Characteristic No. of patients (%)
Weighted mean age ± weighted SD 43.5 ± 12.0 years
Female 13,697 (72.4)
Eligibility criteria
ACR RA alone 8,994 (47.5)
ACR RA + 1 TCM syndromea 3,040 (16.1)
ACR RA + 2 TCM syndromesa 332 (1.8)
ACR RA + ≥3 TCM syndromesa 1,072 (5.7)
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ACR RA + unspecified number TCM
syndromesa
300 (1.6)
ACR RA + TCM syndrome (not guideline-
driven)
5,181 (27.4)
Median disease duration (range) 5.4 years (0.04-28 years)
Interventions
CHM alone 10,108 (53.4)
CHM + DMARDs 1,595 (8.4)
CHM + DMARDs + NSAIDs 511 (2.7)
CHM + DMARDs + steroids + NSAIDs 79 (0.4)
CHM + steroids 501 (2.6)
CHM + steroids + NSAIDs 200 (1.1)
CHM + NSAIDs 2,101 (11.1)
CHM + NSAIDs + antibiotic 74 (0.4)
DMARDs alone 1,402 (7.4)
DMARDs + steroids 78 (0.4)
DMARDs + steroids + NSAIDs 363 (1.9)
DMARDs + NSAIDs 992 (5.2)
NSAIDs + antibiotic 56 (0.3)
NSAIDs alone 644 (3.4)
Antibioticb 50 (0.3)
Placebo alone 165 (0.9)
Previous WM treatmentc 8,518 (45.0)
Most common patterns reportedd
Dampness-heat blockage 1,023 (10.3)
Dampness-cold and qi deficiency-blood stasis 557 (5.6)
Heat-cold complex 512 (5.2)
Dampness-cold blockage 300 (3.0)
Dampness-heat and qi deficiency-blood stasis 269 (2.7)
Qi deficiency and blood stasis 226 (2.3)
Yin deficiency 178 (1.8) aChinese medical syndrome following governmental guidelines.
bPenicillin.
cOnly 49 studies reported data.
dPercentages are based on the 46 studies in which eligibility criteria included diagnosis with at
least 1 TCM syndrome (n = 9,925).
ACR RA = American College of Rheumatology classification criteria for rheumatoid arthritis;
CHM = Chinese herbal medicine; DMARDs = disease-modifying antirheumatic drugs; NSAIDs
= nonsteroidal anti-inflammatory drugs; SD = standard deviation; TCM syndrome = traditional
Chinese medicine syndrome; WM = Western medicine.
Quality assessment
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Supplementary Figure 1 summarizes the results across RCTs. A high risk of bias across all
domains was observed across all domains. When evaluating selection bias, we found that 60% of
the RCTs did not report sufficient detail to evaluate methods of random sequence generation or
allocation concealment (judged unclear). In addition, 21% were judged to have high risk for
selection bias (11% from sequence generation, 30% from allocation concealment). Risk of
performance bias (not blinding participants or personnel) was judged to be high in 85% of the
RCTs, and detection bias (blinding of assessment of primary outcome) was judged to be high in
89% of the RCTs. More than two-thirds of the RCTs did not provide sufficient detail to judge the
risk for attrition bias and lacked data on withdrawal rates, power calculation, and how missing
data was handled. From the remaining RCTs providing details to evaluate attrition bias, 4% were
judged to be of high risk. Risk of reporting bias was high in 40% of the RCTs, and 86% of the
RCTs did not report the source of funding or include a disclosure statement.
RCT determinants associated with high risk of bias
Characteristics observed in RCTs according to risk of bias are shown in Supplementary Table 1.
In the univariate analysis, earlier year of publication, fewer authors, funding source not reported
or disclosed, publication in a language other than English, authors from non-academic settings,
and no power calculation reported were associated with high or unclear risk of bias in various
domains (Table 3). After adjustment for covariates, the following associations remained in the
multivariable analysis: i) earlier year of publication and funding source not reported or disclosed
were associated with high or unclear risk of selection bias (sequence generation); ii) fewer
authors was associated with high or unclear risk of selection bias (allocation concealment),
performance bias, and attrition bias; and iii) publication in a language other than English and
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funding source not reported or disclosed was associated with high or unclear risk of reporting
bias. Logistic regression analysis could not be performed for detection bias owing to the small
number of RCTs in the low risk of bias group (n = 2).
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Table 3. Characteristics of randomized controlled trials (RCTs) included in our study (n = 119) associated with high or unclear risk of
bias
Year of
publication
Sample
size
Number of
authors
Language
Funding source
disclosed Affiliationa
Power calculation
includedb
English Chinese Yes No University
Federal/
State Yes No
Selection bias
(sequence
generation)
Univariate
OR (95% CI) 0.79
(0.70, 0.88)
0.99
(0.99, 1.0)
0.85
(0.75, 0.96) REF
2.6
(0.94, 7.2) REF
7.7
(3.0, 19.8) REF
1.6
(0.74, 3.6) REF
2.2
(0.13, 36.7)
0.0001 0.3 0.01
0.07
<0.0001
0.2
0.6
Multivariable
OR (95% CI) 0.83
(0.73, 0.94) REF
5.0
(1.8, 13.8)
p 0.003
0.002
Selection bias
(allocation
concealment)
Univariate
OR (95% CI) 0.90
(0.77, 1.1)
0.99
(0.99, 1.0)
0.85
(0.75, 0.96) REF
7.4
(1.9, 29.0) REF
4.0
(1.1, 14.9) REF
1.1
(0.29, 4.2) REF
11.4
(0.66, 197.6)
p 0.2 0.1 0.01
0.004
0.04
0.9
0.09
Multivariable
OR (95% CI)
0.85
(0.75, 0.96)
p
0.01
Performance bias
Univariate
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OR (95% CI) 0.87
(0.75, 1.0)
0.99
(0.99, 1.0)
0.83
(0.73, 0.95) REF
7.9
(2.1, 28.5) REF
4.1
(1.2, 14.0) REF
1.2
(0.36, 4.0) REF
51.2
(1.2, 2224.3)
p 0.08 0.2 0.007
0.002
0.02
0.8
0.04
Multivariable
OR (95% CI)
0.83
(0.73, 0.95)
p
0.007
Attrition bias
Univariate
OR (95% CI) 0.83
(0.74, 0.93)
1.0
(0.99, 1.0)
0.68
(0.56, 0.82) REF
2.7
(0.96, 7.7) REF
3.1
(1.2, 7.6) REF
1.5
(0.66, 3.5) REF
15.0
(0.36, 633.8)
p 0.002 0.7 0.0001
0.06
0.02
0.3
0.2
Multivariable
OR (95% CI)
0.68
(0.56, 0.82)
p
0.0001
Reporting bias
Univariate
OR (95% CI) 0.91
(0.83, 1.0)
0.99
(0.99, 1.0)
0.86
(0.76, 0.98) REF
4.9
(1.5, 16.0) REF
3.5 (1.4,
8.9) REF
2.7
(1.3, 5.8) REF
5.8
(0.14, 243.8)
p 0.06 0.3 0.03
0.008
0.008
0.01
0.4
Multivariable
OR (95% CI)
REF
4.1
(1.2, 13.6) REF
3.0
(1.1, 7.7)
p
0.02
0.03 a
Two RCTs written by authors affiliated with the State and a University were considered part of the University for this analysis. bLogistic regression analysis for detection bias was not performed owing to the small number of RCTs that included power calculation
(n = 2).
Abbreviations: OR = odds ratio; CI = confidence interval.
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Adherence to CONSORT standards for TCM
Rates of adherence to CONSORT standards for TCM are shown in Table 4. Most of the RCTs
(98%) stated the objective adequately. However, most RCTs (94%) did not include the
recommended information (specification of interventions, name of disease, and study design) in
the title or abstract. In the introduction sections, more than half (61%) did not provide the three
names of the compound formulation (Chinese, Latin, and English) as recommended by the
World Health Organization. The methods sections of most RCTs were poorly reported (Table 4).
Most RCTs (ranging from 85% to 98%) failed to describe in enough detail the interventions, type
of study design, calculation of sample size, or methods of randomization and blinding. In the
results sections, many RCTs (78%) did not indicate how participants moved through the study
over time or provide a flow diagram as recommended, and 93% of RCTs did not include
intention-to-treat analysis. The discussion sections were compromised in 8 to 83% of the RCTs
owing to a lack of general interpretation of the results and conflict of interest information.
Table 4. Percentage of randomized controlled trials in our analysis (n = 119) not adherent to
reporting standards provided in the Consolidated Standards of Reporting Trials (CONSORT)
statement for traditional Chinese medicine.
CONSORT item
CONSORT
item no. No. (%)
Title and abstract 1 112 (94)
Introduction
Background 2 73 (61)
Objectives 3 2 (2)
Methods
Participants 4 45 (38)
Interventions 5 101 (85)
Outcomes 6 15 (13)
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Type of study design 7 117 (98)
Sample size 8 117 (98)
Randomization
Sequence generation 9 72 (61)
Allocation concealment 10 109 (92)
Implementation 11 111 (93)
Blinding (masking) 12 107 (90)
Statistical methods 13 48 (40)
Results
Participant flow 14 93 (78)
Recruitment 15 33 (28)
Baseline data 16 31 (26)
Numbers analyzed 17 111 (93)
Outcomes and estimation 18 11 (9)
Ancillary analyses 19 23 (19)
Adverse events 20 40 (34)
Discussion
Interpretation 21 9 (8)
Generalizability 22 14 (12)
Overall evidence 23 99 (83)
Subgroup analyses
When comparing the risk of bias from the 90 RCTs published before the Cochrane risk of bias
tool was released in 2008 (year of publication 2000-2008) with that of the 29 RCTs published
later, we observed improvement in RCTs published after 2008 in the following domains:
selection bias (22% compared with 59%, p = 0.0004), attrition bias (18% compared with 52%, p
= 0.0005), and reporting bias (41% compared with 66%, p = 0.02). When comparing adherence
to reporting guidelines from the 80 RCTs published before the CONSORT-TCM statement was
released in 2007 (publication date 2000-2007) with that of the 39 RCTs published later, we
observed improvement in RCTs published after 2007 in most of the items except in reporting
sufficient details about the objectives of the study, design, power calculation, and methods to
avoid bias (data not shown).
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DISCUSSION
Our results indicate that serious methodology and reporting flaws still exist in clinical trials
evaluating the effect of CHM in RA. We found that the potential for selection bias was high;
two-thirds of the RCTs in our analysis lacked sufficient detail on how the random sequence was
generated. Similarly, most RCTs were not blinded (e.g., for participants, personnel, or outcome
assessment), thus increasing the potential for both performance and detection bias. Risk of
attrition bias was high or unclear in more than two-third of the RCTs. Reporting bias was also
judged to be high or unclear in half of the included RCTs owing to a lack of study protocol
and/or reporting less than the minimum number of outcome measures recommended to be
included in RA clinical trials.[148] Furthermore, we found that RCTs that were older, had fewer
authors, did not report or disclose funding, were published in a language other than English, or
were written by authors from non-academic settings, were likely to have a high or unclear risk of
bias methodology in at least one of the evaluated domains.
We also found that adherence to reporting standards remains a concern. Title and
abstract, introduction, and methods were even more problematic. Because of these weaknesses,
readers are not provided with clear and transparent information on the interventions or methods
to assess bias in selecting, masking, and evaluating participants. Other areas of concern were
lack of appropriate general interpretation of the results in the context of current evidence and
incomplete descriptions of conflicts of interest.
It is important to differentiate between the two main concepts reported in this review:
methodological quality and quality of reporting. One of the main components of evidence-based
medicine is the use of available literature to improve decision-making. Stronger inferences can
be drawn from studies in which measures have been taken before, during, and after the
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intervention to prevent random and systematic bias. Although RCTs are ranked high in the
hierarchy of evidence, not all RCTs share the same quality, which can lead to biased results.
Quality of reporting is a separate concern. A lack of complete and transparent reporting of the
processes and findings of an RCT is commonly linked to methodological flaws. Poor reporting
leaves out critical information needed to judge study safeguards against bias.
A few systematic reviews evaluating the efficacy of CHM and reporting on the
methodological quality of the studies have shown similar results. However, none of these studies
evaluated CHMs exclusively (i.e., excluding other TCM) in patients with RA. Nonetheless, a
review evaluating the characteristics of 89 studies published between 2000 and 2003 and indexed
in the CNKI reported a lack of unified diagnostic and evaluating standards.[149] Another review
evaluating 20 RCTs published between 2000 and 2010 showed that methodological quality
according to the Jadad scale was generally low, with an average quality score of 1.2 out of
5.[150] Contrastingly, a Cochrane review evaluating herbal medicines in general (including 3
CHMs) showed that the quality of the studies has improved since 2000, but the risk of bias
across different domains was variable.[151] Furthermore, an overview of 31 reviews published
between 1999 and 2009 evaluating several TCM approaches (including CHMs) for multiple
diseases showed that methodological quality improved over the years, although many issues
remained, specifically a high risk of selection (inadequate randomization methods), attrition
(small sample sizes and high withdrawal rates), and reporting (selective reporting of outcomes)
biases.[152 179]
To the best of our knowledge, the current study is the first appraising both
methodological quality and adherence to reporting standards specifically in RCTs evaluating
CHM in patients with RA. No other studies have analyzed the characteristics associated with a
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high risk of bias or poor adherence to reporting standards. For methodological quality, we used
the risk of bias tool, an instrument endorsed by the Cochrane Collaboration to facilitate improved
appraisal of evidence. The tool has shown significant correlations with other appraisal tools.[153,
154] For example, the risk of bias tool was shown to accurately identify trials that may have
overestimated treatment effects. Studies shown to have a high or unclear risk of bias according to
the risk of bias tool have larger effect estimates than studies shown to have a low risk of
bias.[155]
Our study has certain limitations. First, as with any systematic review, it was constrained
by the available data. For example, a protocol or trial registration was not found for most of the
RCTs included in our review. This is concerning because the validity of the conclusion of an
RCT is largely based on adherence to prespecified methods (including outcomes of interest).
Trial registration could improve transparency and help identify gaps in knowledge, prevent
unnecessary duplication in clinical trials, and improve adherence to international quality
standards.[156] Second, we included studies with substantial variation in characteristics (e.g.,
RA diagnosis, TCM syndromes, and CHM descriptions). However, this allowed us to evaluate a
larger number of RCTs. Third, we did not search the CNKI database, which could have increased
the number of publications included in this review, owing to access barriers. Lastly, independent
quality assessment for non-English language articles could not be performed. Only one reviewer
could translate Chinese articles; therefore, more than 85% of the studies were evaluated by the
translator and cross-checked by another reviewer using the translation from the first reviewer.
In summary, our results indicate that trials of CHM for the treatment of RA often fail to
meet expected methodological criteria, and high-quality evidence is lacking. Because clinical
trials are just below systematic reviews in the hierarchy of evidence and are used to endorse
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recommendations by health organizations, more attention is needed to improve the
methodological robustness of these studies. Future clinical trials evaluating CHMs in RA should
be designed, conducted, and reported according to current specifications and principles.
ACKNOWLEDGMENTS
We are grateful to Yimin Geng from the Research Medical Library of The University of Texas
MD Anderson Cancer Center for helping with the terms included in the search strategies for the
electronic databases and to Ms. Pratibha Nayak for her contributions during the selection of the
studies.
AUTHOR CONTRIBUTIONS
Dr Suarez-Almazor had full access to all of the data in the study and takes responsibility for the
integrity and the accuracy of the data analysis.
Study concept and design: Suarez-Almazor, Lopez-Olivo
Search strategy: Pratt, Geng
Selection of the studies: Pan, Nayak, Lopez-Olivo
Quality appraisal and data extraction: Pan, Lopez-Olivo
Analysis and interpretation of data: Song, Pan, Lopez-Olivo, Suarez-Almazor
Drafting of the manuscript: Pan, Lopez-Olivo, Song, Suarez-Almazor
Critical revision of the manuscript for important intellectual content: Pan, Lopez-Olivo,
Song, Pratt, Suarez-Almazor
Administrative, technical, or material support: Suarez-Almazor
Study supervision: Suarez-Almazor
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SOURCE OF FUNDING
The statistical analysis in this research (through the Biostatistics Resource Group) was supported
in part by a Cancer Center Support Grant from the National Cancer Institute (P30CA016672) to
The University of Texas MD Anderson Cancer Center.
COMPETING INTERESTS
We have read and understood BMJ Open policy on declaration of interests and declare the
following interests. (1) Dr. Suarez-Almazor is the recipient of a K24 career award from the
National Institute for Musculoskeletal and Skin Disorders. (2) Dr. Pan’s work is supported by the
Shanghai Municipal Education Commission and the Shanghai Shuguang Hospital, Shanghai
University of TCM. (3) Dr. Lopez-Olivo is the recipient of a career award from the
Rheumatology Research Foundation and has received a consulting fee from Complete HEOR
Solutions outside the scope of the submitted work. The authors have no other relationships or
activities that could appear to have influenced the submitted work. In addition, none of the
authors has had relationships with companies that might have an interest in the submitted work
in the previous 3 years. The authors’ spouses, partners, or children also have no financial
relationships that may be relevant to the submitted work. None of the authors has any
nonfinancial interests that may be relevant to the submitted work. All authors have completed the
Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request
from the corresponding author).
DATA SHARING
No additional data available.
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FIGURE LEGENDS
Figure 1. Flow chart of included studies. Abbreviations: RA = rheumatoid arthritis; CHM =
Chinese herbal medicine.
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Figure 1
Figure 1
117x127mm (300 x 300 DPI)
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Appendix 1. Medline Strategy
Database(s): Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations and Ovid
MEDLINE(R) 1946 to 06/2015
# Searches
1 RHEUMATOID ARTHRITIS/
2 ((rheumatoid or reumatoid) adj3 (arthriti* or artriti*)).mp.
3 ra.ti.
4 (rheumatism* or rheumarthriti * or antirheumatic* or anti-rheumatic*).ti,ab.
5 ((rheumatic or reumatic) adj3 (arthriti* or polyarthriti*)).ti,ab.
6 rheumat*.jw.
7 or/1-6
8 exp MEDICINE, CHINESE TRADITIONAL/
9 DRUGS, CHINESE HERBAL/
10 TCM.ti.
11 ((China* or Chinese*) adj3 (medicin* or traditional* or natural* or patent*)).mp.
12 ((China* or Chinese*) adj5 herb* adj5 (drug* or prepar* or formula* or pharmac* or
prescri* or mixture* or drink*)).mp.
13 ((China* or Chinese*) adj5 (decoct* or extract* or remedy or remedies or soup* or
infusion*)).mp.
14 ((China* or Chinese*) adj5 (ethnopharm* or phytotherap* or phytomedicin* or
ethnobotanical*)).mp.
15 "Chinese materia medica*".mp.
16 ("zhong yao" or "zhong yi" or "zhongyao" or "zhongyi").mp.
17 or/8-16
18 7 and 17
19 PLANTS, MEDICINAL/
20 ETHNOPHARMACOLOGY/
21 exp PHYTOTHERAPY/
22 exp PLANT PREPARATIONS/
23 exp PLANT ROOTS/
24 plant extracts.rn.
25 or/19-24
26 (China* or Chinese* or "Hong Kong*" or Sino* or Taiwan*).mp.
27 chinese.lg.
28 (China* or Chinese* or "Hong Kong*" or Sino* or Taiwan*).in.
29 (China* or Chinese* or "Hong Kong*" or Taiwan*).jw.
30 (China* or Chinese* or "Hong Kong*" or Taiwan*).cp.
31 or/26-30
32 25 and 31
33 7 and 32
34 TRIPTERYGIUM/
35 ("Tripterygi* wilfordi*" or "thunder god vine*" or "Lei Gong Teng" or LeiGongTeng or
triptolide or celastrol).mp.
36 exp PAEONIA/
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37 (peony* or paeonia* or "Bai Shao" or BaiShao).mp.
38 SAUSSUREA/
39 (Xuelian or Xue Lian or Saussurea).mp.
40 SINOMENIUM/
41 (Zheng Qing Feng Tong Ning or ZhengQing FengTongNing or Sinomeni*).mp.
42 or/34-41
43 7 and 42
44 Tripterygi* Hypoglauc*.mp.
45 Aconit* Kusnezofi*.mp.
46 Aconit* Carmichael*.mp.
47 Cyathul*.mp.
48 Clematid*.mp.
49 Rehmanni*.mp.
50 Spatholob*.mp.
51 Seolopendr*.mp.
52 Scorpio*.mp.
53 Stephani*.mp.
54 Ephedr*.mp.
55 Glycyrrhiz*.mp.
56 Angelic* Sinensi*.mp.
57 Gentian* Macrophyll*.mp.
58 Astragal*.mp.
59 Asari*.mp.
60 Notopterygi*.mp.
61 (Chuanxiong* or Chuan xiong*).mp.
62 Saposhnikovi*.mp.
63 Angelic* Pubescent*.mp.
64 Lateral* Praeparat*.mp.
65 Cinnamom*.mp.
66 Anemarrhen*.mp.
67 Paeoni* Alba*.mp.
68 Terminali*.mp.
69 Cartham*.mp.
70 or/44-69
71 7 and 70
72 (San Zi Yang Qin* or SanZiYangQin*).mp.
73 (Huo Luo Xiao Ling* or HuoLuoXiaoLing*).mp.
74 (Yi Wei* or YiWei*).mp.
75 (Sheng Yang Yi Wei* or ShengYangYiWei*).mp.
76 (San Miao Wan* or SanMiaoWan*).mp.
77 (Si Ni* or SiNi).mp.
78 (Dang Gui Si Ni* or DangGuiSiNi*).mp.
79 (Wu Tou* or WuTou*).mp.
80 (Shen Tong Zhu Yu* or ShenTongZhuYu*).mp.
81 (Huang Qi Gui Zhi Wu Wu* or Huang QiGuiZhiWuWu*).mp.
82 (Bai Hu Jia Gui Zhi* or BaiHuJiaGuiZhi*).mp.
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83 (Xuan Bi* or XuanBi*).mp.
84 (Du Huo Ji Sheng* or DuHuoJiSheng*).mp.
85 (Si Wu* or SiWu*).mp.
86 (Tao Hong si Wu* or TaoHongSiWu*).mp.
87 (Gui Zhi* or GuiZhi*).mp.
88 (Juan Bi* or JuanBi*).mp.
89 (Xiao Huo Luo* or XiaoHuoLuo*).mp.
90 (Ma Huang Fu Zi Gan Cao* or MaHuangFuZiGanCao*).mp.
91 (Fu Zi* or FuZi).mp.
92 (Fang Feng* or FangFeng*).mp.
93 (Yi Yi Ren* or YiYiRen*).mp.
94 (Si Jun Zi* or SiJunZi*).mp.
95 (Xiao Jian Zhong* or XiaoJianZhong*).mp.
96 (Huang Qi Jian Zhong* or HuangQiJianZhong*).mp.
97 (San Bi* or SanBi).mp.
98 (Yang He* or YangHe*).mp.
99 (Ren Shen Yang Rong* or RenShenYangRong*).mp.
100 (Bai Hu* or BaiHu).mp.
101 (Qing Ying* or QingYing*).mp.
102 (Tong Xie Yao Fang* or TongXieYaoFang*).mp.
103 (Xue Fu Zhu Yu* or XueFuZhuYu*).mp.
104 or/72-103
105 7 and 104
106 (Chuan Xiong Qin* or ChuanXiongQin*).mp.
107 (Huang Qi* or HuangQi*).mp.
108 (Shi Re Bi* or ShiReBi*).mp.
109 (Zhuang Gu* or ZhuangGu*).mp.
110 (Pan Long Qi* or PanLongQi*).mp.
111 (Kun Ming Shan Hai Tang* or KunMingShanHaiTang*).mp.
112 (Zheng Qing Feng Tong Ning* or ZhengQingFengTongNing*).mp.
113 (Yu Xue Bi* or YuXueBi*).mp.
114 (Han Shi Bi* or HanShiBi*).mp.
115 (Lei Gong Teng* or LeiGongTeng*).mp.
116 (Lei Gong Teng Duo Dai* or LeiGongTengDuoDai*).mp.
117 (Huo Luo* or HuoLuo*).mp.
118 (Bao An Wan Ling* or BaoAnWanLing*).mp.
119 (Shou Feng Shun Qi* or ShouFengShunQi*).mp.
120 (Feng Shi* or FengShi*).mp.
121 (Gu Ci Xiao Tong* or GuCiXiaoTong*).mp.
122 (Fu Fang Xia Tian Wu* or FuFangXiaTianWu*).mp.
123 (Xia Tian Wu* or XiaTianWu*).mp.
124 (Er Xian* or ErXian*).mp.
125 (Zhui Feng Tou Gu* or ZhuiFengTouGu*).mp.
126 (Hong Hua* or HongHua*).mp.
127 (She Xiang Zhui Feng* or SheXiangZhuiFeng*).mp.
128 (Zhui Feng* or ZhuiFeng*).mp.
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130 (Xiao Huo Luo* or XiaoHuoLuo*).mp.
131 or/106-130
132 7 and 131
133 (zushima* or zu shi ma*).mp.
134 (biqi* or bi qi*).mp.
135 (wangbi* or wang bi*).mp.
136 Yishen Juanbi*.mp.
137 Yi shen Juan bi*.mp.
138 Shiguogong*.mp.
139 Shi guo gong*.mp.
140 Yunnan Baiyao*.mp.
141 Yun nan Bai yao*.mp.
142 Daphne*.mp.
143 Feng Shi*.mp.
144 FengShi*.mp.
145 or/133-144
146 7 and 145
147 18 or 33 or 43 or 71 or 105 or 132 or 146
148 (animals not (humans and animals)).sh.
149 147 not 148
150 (case reports not (case reports and review)).pt.
151 case report*.ti. not review.pt.
152 150 or 151
153 149 not 152
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Supplementary Figure 1. Risk of bias across studiesa.
0% 20% 40% 60% 80% 100%
Reporting bias
Attrition bias
Detection bias
Performance bias
Selection bias
Low Unclear High
aEvaluated using the Cochrane Risk of Bias Assessment Tool [1]
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Supplementary Table 1. Study characteristics according to type of risk of bias judgment*.
Risk Year,
mean±SD Sample Size, mean±SD
Authors, mean±SD
Impact Factor,
**
mean±SD
Non-English
Language, n (%)
No source of
funding, n (%)
Non-Academic setting,
***
n (%)
No Power Calculation,
n (%)
Selection bias (random sequence) High/Unclear (n=82)
2005 ± 3.6 130.5 ± 197.4 3.7 ± 2.6 0.48 ± 0.45 73 (89%) 73 (89%) 54 (65.9%) 81 (98.8%)
Low (n=37)
2008.5 ± 3.7 222.1 ± 610.8 6.1 ± 6.0 1.8 ± 3.2 28 (75.7%) 19 (51.4%) 20 (54.1%) 36 (97.3%)
p-Value <0.0001 0.6 0.007 <0.0001 0.06 <0.0001 0.2 0.5 Selection bias (allocation concealment) High/Unclear (n=109)
2006 ± 3.8 111.4 ± 73.2 4.0 ± 3.6 0.62 ± 0.95 96 (88.1%) 87 (79.8%) 68 (62.4%) 108 (99.1%)
Low (n=10)
2007.7 ± 4.6 677 ± 1215.4 8.9 ± 6.1 4.0 ± 5.2 5 (50%) 5 (50%) 6 (60%) 9 (90%)
p-Value 0.3 0.3 0.002 0.0005 0.007 0.05 1 0.2 Performance bias High/Unclear (N=107)
2006 ± 3.8 141.8 ± 361.8 4.0 ± 3.6 0.60 ± 0.94 95 (88.8%) 86 (80.4%) 67 (62.6%) 107 (100%)
Low (N=12)
2008 ± 4.2 312.1 ± 487.3 8.8 ± 5.9 3.6 ± 4.8 6 (50%) 6 (50%) 7 (58.3%) 10 (83.3%)
p-Value 0.09 0.3 0.0008 0.0002 0.003 0.03 0.8 0.009 Detection bias High/Unclear (N=117)
2006 ± 3.9 156.2 ± 379.7 4.2 ± 3.2 0.83 ± 1.8 100 (85.5%) 91 (77.8%) 73 (62.4%) 115 (98.3%)
Low (N=2)
2011 ± 4.2 323 ± 164.1 18.5 ± 19.1 4.8 ± 6.4 1 (50%) 1 (50%) 1 (50%) 2 (100%)
p-Value 0.09 0.04 0.09 0.5 0.3 0.4 1 1 Attrition bias High/Unclear (N=88)
2005.5 ± 3.6 166.4 ± 435.2 3.4 ± 2.0 0.50 ± 0.45 78 (88.6%) 73 (83%) 57 (64.8%) 88 (100%)
Low (N=31)
2008 ± 4.2 138.0 ± 100.6 7.5 ± 6.4 2.0 ± 3.5 23 (74.2%) 19 (61.3%) 17 (54.8%) 29 (93.5%)
p-Value 0.003 0.1 <0.0001 <0.0001 0.08 0.01 0.3 0.07 Reporting bias
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High/Unclear (N=63)
2005.6 ± 3.6 113.7 ± 78.5 3.6 ± 4.1 0.55 ± 1.2 59 (93.7%) 55 (87.3%) 46 (73%) 63 (100%)
Low (N=56)
2007± 4.1 209.9 ± 541.8 5.4 ± 3.9 1.3 ± 2.5 42 (75%) 37 (66.1%) 28 (50%) 54 (96.4%)
p-Value 0.1 0.9 0.0004 <0.0001 0.005 0.006 0.01 0.2 *Studies classified as unclear risk of bias were merged to the high risk group
**IF (2013) or CNKI was used
*** There are two affiliated with State and University classified as University
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PRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 Checklist
Section/topic # Checklist item Reported on page #
TITLE
Title 1 Identify the report as a systematic review, meta-analysis, or both. 1
ABSTRACT
Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.
4-5
INTRODUCTION
Rationale 3 Describe the rationale for the review in the context of what is already known. 7-8
Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).
8
METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
NA
Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered,
language, publication status) used as criteria for eligibility, giving rationale. 9
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.
8-9
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.
Suppl. File
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
9
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
9-10
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
10
Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
10
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). 11
Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency
(e.g., I2) for each meta-analysis.
11
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PRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 Checklist
Page 1 of 2
Section/topic # Checklist item Reported on page #
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
10
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
11
RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
12 & Figure 1
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
12 & Table 1
Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). 16
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
NA
Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. 17 & Table 3
Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Suppl. Fig.
Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). 22
DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).
23
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).
25
Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. 25
FUNDING
Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.
2
From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(6): e1000097. doi:10.1371/journal.pmed1000097
For more information, visit: www.prisma-statement.org. Page 2 of 2
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Systematic Review of the Methodological Quality of Controlled Trials Evaluating Chinese Herbal Medicine in
Patients with Rheumatoid Arthritis
Journal: BMJ Open
Manuscript ID bmjopen-2016-013242.R1
Article Type: Research
Date Submitted by the Author: 01-Dec-2016
Complete List of Authors: Pan, Xin; Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Department of Rheumatology Lopez-Olivo, M; The University of Texas MD Anderson Cancer Center
Song, Juhee; The University of Texas, MD Anderson Cancer Center, Department of Biostatistics Pratt, Gregory; The University of Texas, MD Anderson Cancer Center, Research Medical Library Suarez-Almazor, Maria; The University of Texas MD Anderson Cancer Center, General Internal Medicine
<b>Primary Subject Heading</b>:
Rheumatology
Secondary Subject Heading: Research methods, Complementary medicine, Evidence based practice, Medical publishing and peer review
Keywords: Chinese herbal medicine, Quality of randomized controlled trials, Traditional Chinese medicine, Systematic review, Rheumatoid arthritis
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1
Systematic Review of the Methodological Quality of Controlled Trials Evaluating Chinese
Herbal Medicine in Patients with Rheumatoid Arthritis
Xin Pan1, Maria A. Lopez-Olivo
2, Juhee Song
3, Gregory Pratt
4, Maria E. Suarez-Almazor
2.
1Department of Rheumatology, Shuguang Hospital, Shanghai University of Traditional Chinese
Medicine, Shanghai, China; 2Department of General Internal Medicine, Rheumatology Section,
3Department of Biostatistics, and
4Research Medical Library, The University of Texas MD
Anderson Cancer Center, Houston, TX 77030, USA.
Corresponding Author: Maria E. Suarez-Almazor, MD, PhD, Department of General Internal
Medicine, Unit 1467, The University of Texas MD Anderson Cancer Center, 1515 Holcombe
Boulevard, Houston, TX 77030, USA. Phone: 713-563-6209. Fax: 713-563-4491. Email:
msalmazor@mdanderson.org.
The Corresponding Author has the right to grant on behalf of all authors and does grant on
behalf of all authors a worldwide licence to the Publishers and its licensees in perpetuity, in all
forms, formats, and media (whether known now or created in the future), to i) publish,
reproduce, distribute, display, and store the Contribution; ii) translate the Contribution into
other languages, create adaptations, create reprints, include the Contribution within collections,
and create summaries, extracts, or abstracts of the Contribution; iii) create any other derivative
work(s) based on the Contribution; iv) exploit all subsidiary rights in the Contribution; v)
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2
include electronic links from the Contribution in third party material wherever it may be located;
and vi) licence any third party to do any or all of the above.
Word count: 3,708
Number of figures: 1
Number of tables: 4
Number of references: 151
Number of supplementary files: 1
SOURCE OF FUNDING
The statistical analysis in this research (through the Biostatistics Resource Group) was supported
in part by a Cancer Center Support Grant from the National Cancer Institute (P30CA016672) to
The University of Texas MD Anderson Cancer Center.
COMPETING INTERESTS
We have read and understood BMJ Open policy on declaration of interests and declare the
following interests. (1) Dr. Suarez-Almazor is the recipient of a K24 career award from the
National Institute for Musculoskeletal and Skin Disorders. (2) Dr. Pan’s work is supported by the
Shanghai Municipal Education Commission and the Shanghai Shuguang Hospital, Shanghai
University of TCM. (3) Dr. Lopez-Olivo is the recipient of a career award from the
Rheumatology Research Foundation and has received a consulting fee from Complete HEOR
Solutions outside the scope of the submitted work. The authors have no other relationships or
activities that could appear to have influenced the submitted work. In addition, none of the
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3
authors has had relationships with companies that might have an interest in the submitted work
in the previous 3 years. The authors’ spouses, partners, or children also have no financial
relationships that may be relevant to the submitted work. None of the authors has any
nonfinancial interests that may be relevant to the submitted work. All authors have completed the
Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request
from the corresponding author).
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ABSTRACT
Objectives: We appraised the methodological and reporting quality of randomized controlled
clinical trials (RCTs) evaluating the efficacy and safety of Chinese herbal medicine (CHM) in
patients with rheumatoid arthritis (RA).
Design: For this systematic review, electronic databases were searched from inception until June
2015. The search was limited to humans and non-case report studies, but was not limited by
language, year of publication, or type of publication. Two independent reviewers selected RCTs,
evaluating CHM in RA (herbals and decoctions). Descriptive statistics were used to report on
risk of bias and their adherence to reporting standards. Multivariable logistic regression analysis
was performed to determine study characteristics associated with high or unclear risk of bias.
Results: Out of 2,342 unique citations, we selected 119 RCTs including 18,919 patients: 10,108
patients received CHM alone and 6,550 received 1 of 11 treatment combinations. A high risk of
bias was observed across all domains: 21% had a high risk for selection bias (11% from
sequence generation, 30% from allocation concealment), 85% for performance bias, 89% for
detection bias, 4% for attrition bias, and 40% for reporting bias. In multivariable analysis, fewer
authors was associated with selection bias (allocation concealment), performance bias, and
attrition bias, and earlier year of publication and funding source not reported or disclosed were
associated with selection bias (sequence generation). Studies published in non-English language
were associated with reporting bias. Poor adherence to recommended reporting standards (less
than 60% of the studies not providing sufficient information) was observed in 11 of the 23
sections evaluated.
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Limitations: Study quality and data extraction were performed by one reviewer and cross-
checked by a second reviewer. Translation to English was performed by one reviewer in 85% of
the included studies.
Conclusions: Studies evaluating CHM often fail to meet expected methodological criteria, and
high-quality evidence is lacking.
Keywords: traditional Chinese medicine, Chinese herbal medicine, rheumatoid arthritis,
randomized controlled trial, systematic review
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STRENGTHS OF THIS STUDY
1. First study appraising both methodological quality and adherence to reporting standards
specifically in RCTs evaluating Chinese herbal medicines in patients with rheumatoid
arthritis. No other studies have analyzed the characteristics associated with a high risk of
bias or poor adherence to reporting standards.
2. For methodological quality, we used the risk of bias tool, an instrument endorsed by the
Cochrane Collaboration to facilitate improved appraisal of evidence. The tool has shown
significant correlations with other appraisal tools.
3. For reporting adequacy, we used the CONSORT statement which is a minimum set of
recommendations for reporting randomized trials. It was developed by a team of
international experts and is widely used worldwide and encouraged by the leading
journals for the reporting of trials (over 50% of the core medical journals listed in the
Abridged Index Medicus on PubMed - e.g., BMJ, BMJ Open, New England Journal of
Medicine, Journal of the American Medical Association).
LIMITATIONS OF THIS STUDY
4. We did not search the Chinese Medical databases.
5. More than 85% of the studies were evaluated by the translator and cross-checked by
another reviewer using the translation from the first reviewer.
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ARTICLE SUMMARY
1. First study appraising both methodological quality and adherence to reporting standards
specifically in RCTs evaluating Chinese herbal medicines in patients with rheumatoid
arthritis.
2. Serious methodological and reporting flaws still exist in RCTs evaluating the effects of
Chinese herbal medicines in rheumatoid arthritis. Potential for selection bias was high
across all domains evaluated and adherence to reporting standards is still a concern.
3. Earlier year of publication, fewer authors, funding not reported or disclosed, and
publication in a language other than English were the study characteristics associated
with risk of bias.
4. Our systematic review is constrained by the available resources and data.
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INTRODUCTION
Rheumatoid arthritis (RA) is one of the leading causes of disability worldwide, affecting
1% of the world population. According to the Global Burden of Disease 2010 Study, years lived
with disability from RA increased from 2’566,000 in 1990 to 3’776,000 in 2010.[1] With aging
populations throughout the world, and declines in mortality, the number of people living with
RA will increase substantially over coming decades.
Chinese herbal medicines (CHMs) have been used to treat rheumatoid arthritis (RA) for
many years, mostly in Asia. The use of CHMs is generally based on experience and is influenced
by a holistic concept of health.[2] In traditional Chinese medicine (TCM), RA belongs to the
category of “bi syndrome;” i.e., it is believed to be caused by attacks of wind, cold, dampness, or
heat, which cause disharmony between bodily systems.[3, 4] Patients are classified as having a
particular TCM syndrome according to their symptoms and then treated with CHMs to decrease
inflammation by restoring the affected system or to ameliorate the side effects of disease-
modifying antirheumatic drugs.[5] TCM guidelines have been developed by the Chinese
government for the diagnosis and treatment of these syndromes [6-8].
There are numerous CHM preparations for the treatment of RA, including decoctions,
whole plants, plant extracts, and patented formulas,[9-11] all of which can be given as a single
herb or a mixture of herbs.[12] Patented CHMs are often offered as chemical preparations,
tablets, and capsules with simple and convenient dosing schedules and reduced aftertaste.[2, 12]
This has increased the acceptance of CHM in Western countries. In 2002, a national survey
conducted in the United States reported that almost 20% of adults had used herbal therapies in
the past year.[13] In the United Kingdom, a systematic review of 89 surveys on the use of
complementary medicine showed that more than 50% of respondents with a chronic condition
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reported using this type of medicine during their lifetime.[14] Furthermore, the use rate of herbal
therapies in patients with arthritis in US primary care settings has been reported to be as high as
90%.[15]
After the introduction of evidence-based medicine in China, several randomized
controlled trials (RCT) were conducted to evaluate the efficacy of CHMs for RA.[10, 12, 16, 17]
However, the methodology used to conduct these trials was inconsistent, and the results were
conflicting. Quality of reporting is intrinsically linked to the methodological quality of RCTs.
Criteria for standardization facilitate complete and transparent reporting and help to improve
critical appraisal and interpretation of an RCT. Since the development of the Consolidated
Standards of Reporting Trials (CONSORT) statement in 1996, most high-impact journals have
endorsed its use to improve reporting of RCTs.[18] In 2006, the CONSORT extension for
reporting herbal medicines was developed, and in 2007, a draft of the extension for reporting
TCM was released.[19]
To date, no systematic review has explored the study characteristics associated with
methodological quality in controlled trials (randomized or not) evaluating the efficacy,
effectiveness, or safety of CHMs in the treatment of RA. The objectives of our study were to
appraise the methodological quality of these studies by ascertaining potential risk of bias, to
identify publication factors associated with methodological flaws, and to determine the quality of
reporting according to CONSORT recommendations.
METHODS
We report our methods and results according to the Preferred Reporting Items for Systematic
Review and Meta-Analysis statement.
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Information sources
We searched electronic databases (Medline, EMBASE, Cochrane Library, and Web of Science)
from inception through June 2015 for studies evaluating the use of CHM, including herbals or
decoctions (e.g., “tang”), in patients with RA (search terms are listed in Appendix 1). Our search
was restricted to human studies and excluded case reports but was not limited by language, year
of publication, or type of publication. We also searched the reference lists of potentially relevant
citations (controlled trials and reviews, although reviews themselves were later excluded from
the analysis) to identify additional studies that were not published or otherwise found. EndNote
X6 and DistillerSR were used to manage the records retrieved.
Study selection and eligibility criteria
Two reviewers (X.P. and Pratibha Nayak) independently screened the titles and abstracts of all
citations obtained by our searches. They resolved any disagreements through discussion and
consensus. When no consensus was reached, a third party acted as an adjudicator (M.L.-O.). We
included any RCT evaluating the efficacy, effectiveness, or safety of CHMs in adult patients (age
≥18 years) with RA. All types of CHMs were considered: (i) patented medicines (pharmaceutical
preparation or formulations) made from herbs (e.g., tablets, liquids, granules, plasters, injections,
capsules), (ii) herbal decoctions (e.g., “tang”), and (iii) plants (whole or extracts). Any type of
drug and placebo comparison and any follow-up duration were considered for inclusion. We
excluded retrieved studies that were published before the year 2000, because the most currently
utilized guidelines for reporting clinical trials (i.e., CONSORT statement) were published in
1996, and we conservatively considered four years to be enough time for these guidelines to be
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disseminated and implemented.[18] We also excluded studies published only as abstracts, studies
with a non-RA control group, and subanalyses of parent studies.
Data collection and outcome measures
One author (X.P.) extracted the data, which were then cross-checked by another author (M.L.-
O.). A standardized extraction form was used to collect information about the characteristics of
the RCTs and their participants, types of interventions, reported outcomes, and sources of
funding. Our primary outcome measures were the methodological and reporting quality of the
RCTs.
Methodological quality in individual studies
The quality of each selected RCT was evaluated independently by two reviewers using the
Cochrane risk of bias tool [20] for RCTs published in English. RCTs published in non-English
languages were translated and evaluated by one reviewer (X.P.) and cross-checked by another
(M.L.-O.). In brief, each RCT was evaluated for its potential bias in five domains: selection,
performance, detection, attrition, and reporting. These domains specifically evaluate how the
random sequence was generated, methods of allocation concealment, blinding of participants and
personnel, blinding of the outcome assessment, how incomplete outcome data was handled, and
if there was evidence of selective outcome reporting. Each potential source of bias was graded as
low, unclear, or high, and a justification for each judgment was provided.
Quality of reporting
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We examined how closely the RCTs adhered to reporting standards using the CONSORT
statement for TCM,[21] which focuses only on CHM (i.e., acupuncture, moxibustion, cupping,
and massage are not considered). It is a 23-item checklist, and the major recommendations for
transparent reporting are i) title and abstract should reflect the unique aspects of TCM, ii)
rationale of formulation selection should be described, iii) diagnostic criteria should be specified
for both TCM and conventional medicine, iv) detailed information on the treatment and control
interventions should be included, v) the outcome in TCM terms should be included, and vi) the
ethics approval number and trial registration number should be included.
Summary measures and synthesis of results
Descriptive statistics were used to report RCT and participant characteristics, as well as the
methodological quality of the RCTs. Risk of bias assessment was summarized per domain.
Bivariate analysis was used to compare RCT characteristics according to the risk of bias
judgment. Univariate and multivariable logistic regressions were performed to determine the
factors associated with high or unclear risk of bias in the five domains in RCTs. We combined
the unclear and high risk of bias categories for the analyses. Evidence suggests that the
magnitude of treatment effects may be similar in studies appraised as having high or unclear risk
of bias, but not for studies assessed as low risk of bias.[22] The variables tested as predictors
were year of publication, sample size, number of authors, publication language (English or non-
English), reporting or disclosing of funding (yes or no), and setting (academic or non-academic).
Variables with a univariate p value <0.15 were initially included in a multivariable logistic
regression model and reduced using the stepwise selection method. Associations were described
using odds ratios (ORs) and their associated 95% confidence intervals (CIs). We categorized
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each CONSORT TCM checklist item as reported or not reported.[21, 23] We then summarized
our findings in five sections: title/abstract, introduction, methods, results, and discussion.
Subgroup analyses were performed to compare rates of potential bias (low risk or unclear/high
risk, unclear versus high risk) and adherence to reporting guidelines according to (i) publication
before or after the Cochrane risk of bias tool was released and (ii) publication before or after the
CONSORT statement for TCM was released. SAS version 9.3 (SAS Institute, Inc., Cary, NC)
was used to carry out the computations for all analyses. Apart from the univariate analysis, p <
0.05 was considered statistically significant.
RESULTS
RCT selection
Out of 2,342 unique citations, 232 full-text articles were retrieved to assess for eligibility. Of
those, 119 RCTs were included [24-142] evaluating 18,919 patients. Figure 1 shows the number
of studies screened, assessed for eligibility, and included in the review, with reasons for
exclusion at each stage.
Characteristics of the included studies
Table 1 shows the aggregated characteristics of the included RCTs, and Supplementary Table 1
shows the characteristics of the individual studies. Two-thirds of the RCTs were published
before the CONSORT statement for TCM and herbal interventions was published (2000-2007).
One RCT was conducted in the United States, one in Korea, and the rest in China. Most were
single-center studies and were not indexed in the ISI Web of Knowledge database but were
indexed in the China National Knowledge Infrastructure database (CNKI).
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Outcomes reported varied across RCTs. More than half of the RCTs assessed efficacy
(e.g., disease activity score either 28 [143] or 44; [144] 20%, 30%, 50%, or 70% improvement,
according to American College of Rheumatology criteria,[145] in tender or swollen joint counts,
physician global assessment, or grip strength; or good to moderate improvement according to
European League Against Rheumatism criteria),[146] laboratory outcomes (e.g., erythrocyte
sedimentation rate, C-reactive protein, rheumatoid factor, or anti-cyclic citrullinated peptides), or
adverse events. However, less than 56% of RCTs reported on patient-reported outcomes (e.g.,
pain, patient global assessment, health assessment questionnaire, or morning stiffness), and only
3% reported radiographic outcomes (e.g., Sharp score, erosion, joint narrowing, marked
radiographic progression, or no progression). Thirty-one RCTs (26%) reported improvement of
symptoms but did not provide additional details on the type of symptoms or how these symptoms
were assessed.
Table 1. Summary of characteristics of the randomized controlled trials (RCTs) included in our
analysis (n = 119).
RCT characteristic No. of RCTs (%)a
Duration
Less than 6 months 93 (78)
More than 6 months 23 (19)
Not reported 3 (3)
Year
2000-2007 (before CONSORT TCM)[19, 23, 147] 80 (67)
2008-2014 39 (33)
Language
English 18 (15)
Chinese 101 (85)
Country
China 117 (98)
Korea 1 (1)
United States 1 (1)
Scope
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Single-center 108 (91)
Multicenter 11 (9)
Impact Factor 2013
Web of Science (score range from 0.59 to 2.711) 13 (11)
Web of Science (score range from 7.871 to 16.104) 4 (3)
Indexed in CNKI (score range from 0.031 to 1.068) 101 (85)
Not indexedb 1 (1)
Outcomesc
Disease activity score 15 (13)
ACR 20/30 28 (24)
Tender joint count 72 (61)
Swollen joint count 78 (66)
Health assessment questionnaire 19 (16)
Pain 53 (45)
Morning stiffness 66 (55)
Laboratory outcomes (ESR, CRP, RF, or anti-CCP) 91 (76)
Radiographic outcomes 3 (3)
Discontinuations 51 (43)
Adverse eventsd 76 (64)
Funding 27 (23)
CHM preparation (main intervention)
Plant or extract (one herb) 3 (3)
Decoction alone 15 (13)
Decoction + patented 2 (2)
Individualized (not following guidelines or with
modifications)
52 (44)
Patented 43 (36)
Patented + individualized 4 (3)
Most common CHM (>1 study)
Tripterygium wilfordii/Tripterygium polyglycosides (alone
or combined)
15 (13)
JuanBi decoction/mixture or Yishen JuanBi capsule
(including those with changes or combined)
11 (9)
Feng Shi decoction/granules/wine/injection (including
those with changes or combined)
10 (8)
Total glucosides of peony 6 (5)
Xinfeng capsule 4 (3)
Zhengqing Fengtongning (alone or combined) 4 (3)
Bi Qi capsule 3 (3)
Lugua polypeptide injection 3 (3)
Guizhi Shaoyao Zhimu decoction 3 (3)
Tongbi (tablets or decoction) 3 (3)
Xiatianwu 3 (3)
Bizhongxiao 2 (2)
Sanbi decoction 2 (2)
Shi Re Bi granule/mixture 2 (2)
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Siwu wuteng decoction 2 (2)
Unspecified (including decoctions without a name) 11 (9) aPercentages have been rounded.
bNot indexed in Web of Science or CNKI.
cRCTs can report on one or more outcomes.
dIncluding either clinical safety or laboratory parameters (alanine transaminase, aspartate
transaminase, creatinine, white blood cell count, platelet count, or hemoglobin).
Abbreviations: ACR 20/30 = American College of Rheumatology criteria for improvement at
20% or 30%; anti-CCP = anti-cyclic citrullinated peptide antibodies; CHM = Chinese herbal
medicine; CNKI = China National Knowledge Infrastructure database; CONSORT TCM =
Consolidated Standards of Reporting Trials statement for traditional Chinese medicine (including
herbal interventions); CRP = C-reactive protein; ESR = erythrocyte sedimentation rate; RF =
rheumatoid factor.
Characteristics of the participants and interventions
Most participants included in the RCTs met the 1987 American College of Rheumatology
diagnostic criteria for RA.[148] One RCT included only patients meeting the 2010 ACR
classification criteria [149] and in another RCT patients included met either the 1987 or 2010
criteria. In addition, 52.5% of the participants met the criteria for one or more of the traditional
TCM “pathological factors” or syndromes (i.e., feng [wind], shi [damp], tan [phlegm], re [heat],
qi, or yin deficiency). The most common pathological factors reported are listed in Table 2. A
total of 10,108 patients received a single CHM and 6,550 received 1 of 11 treatment
combinations. Of those receiving combination treatment, 5,061 patients received combinations
that included CHMs (with disease-modifying antirheumatic drugs, nonsteroidal anti-
inflammatory drugs, steroids, or antibiotics). More than half of the CHMs were individualized
preparations targeting pain relief and improvement in joint function. In the control groups, 1,402
patients received disease-modifying antirheumatic drugs alone, (i.e., methotrexate, leflunomide,
sulfasalazine, or etanercept), 644 received nonsteroidal anti-inflammatory drugs alone, and 165
received an inert placebo. In 35 studies, patients were described as having active disease, and
two RCTs included patients with refractory disease, one included patients with early RA, three
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included patients at intermediate stages of RA, and one included patients with both RA and
anemia. Discontinuation rates were not reported in 68 RCTs, but in those that reported
discontinuation rates, they ranged from 0% to 55%.
Table 2. Characteristics of the participants in the 119 randomized controlled trials included in
our analysis (n = 18,919, ranging from 30 to 3,789 patients per trial)
Characteristic No. of patients (%)
Weighted mean age ± weighted SD 43.5 ± 12.0 years
Female 13,697 (72.4)
Eligibility criteria
ACR RA alone 8,994 (47.5)
ACR RA + 1 TCM syndromea 3,040 (16.1)
ACR RA + 2 TCM syndromesa 332 (1.8)
ACR RA + ≥3 TCM syndromesa 1,072 (5.7)
ACR RA + unspecified number TCM
syndromesa
300 (1.6)
ACR RA + TCM syndrome (not guideline-
driven)
5,181 (27.4)
Median disease duration (range) 5.4 years (0.04-28 years)
Interventions
CHM alone 10,108 (53.4)
CHM + DMARDs 1,595 (8.4)
CHM + DMARDs + NSAIDs 511 (2.7)
CHM + DMARDs + steroids + NSAIDs 79 (0.4)
CHM + steroids 501 (2.6)
CHM + steroids + NSAIDs 200 (1.1)
CHM + NSAIDs 2,101 (11.1)
CHM + NSAIDs + antibiotic 74 (0.4)
DMARDs alone 1,402 (7.4)
DMARDs + steroids 78 (0.4)
DMARDs + steroids + NSAIDs 363 (1.9)
DMARDs + NSAIDs 992 (5.2)
NSAIDs + antibiotic 56 (0.3)
NSAIDs alone 644 (3.4)
Antibioticb 50 (0.3)
Placebo alone 165 (0.9)
Previous WM treatmentc 8,518 (45.0)
Most common patterns reportedd
Dampness-heat blockage 1,023 (10.3)
Dampness-cold and qi deficiency-blood stasis 557 (5.6)
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Heat-cold complex 512 (5.2)
Dampness-cold blockage 300 (3.0)
Dampness-heat and qi deficiency-blood stasis 269 (2.7)
Qi deficiency and blood stasis 226 (2.3)
Yin deficiency 178 (1.8) aChinese medical syndrome following governmental guidelines.
bPenicillin.
cOnly 49 studies reported data.
dPercentages are based on the 46 studies in which eligibility criteria included diagnosis with at
least 1 TCM syndrome (n = 9,925).
ACR RA = American College of Rheumatology classification criteria for rheumatoid arthritis;
CHM = Chinese herbal medicine; DMARDs = disease-modifying antirheumatic drugs; NSAIDs
= nonsteroidal anti-inflammatory drugs; SD = standard deviation; TCM syndrome = traditional
Chinese medicine syndrome; WM = Western medicine.
Quality assessment
Supplementary Figure 1 summarizes the results across RCTs. A high risk of bias across all
domains was observed across all domains. When evaluating selection bias, we found that 29% of
the RCTs did not report sufficient detail to evaluate methods of random sequence generation or
in 31% allocation concealment (judged unclear). In addition, 21% were judged to have high risk
for selection bias (11% from sequence generation, 30% from allocation concealment). Risk of
performance bias (not blinding participants or personnel) was judged to be high in 85% of the
RCTs, and detection bias (blinding of assessment of primary outcome) was judged to be high in
89% of the RCTs. More than two-thirds of the RCTs did not provide sufficient detail to judge the
risk for attrition bias and lacked data on withdrawal rates, power calculation, and how missing
data was handled. From the remaining RCTs providing details to evaluate attrition bias, 4% were
judged to be of high risk. Risk of reporting bias was high in 40% of the RCTs, and 86% of the
RCTs did not report the source of funding or include a disclosure statement.
RCT determinants associated with high risk of bias
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Characteristics observed in RCTs according to risk of bias are shown in Supplementary Table 2.
In the univariate analysis, earlier year of publication, fewer authors, funding source not reported
or disclosed, publication in a language other than English, authors from non-academic settings,
and no power calculation reported were associated with high or unclear risk of bias in various
domains (Table 3). After adjustment for covariates, the following associations remained in the
multivariable analysis: i) earlier year of publication and funding source not reported or disclosed
were associated with high or unclear risk of selection bias (sequence generation); ii) fewer
authors was associated with high or unclear risk of selection bias (allocation concealment),
performance bias, and attrition bias; and iii) publication in a language other than English and
funding source not reported or disclosed was associated with high or unclear risk of reporting
bias. Logistic regression analysis could not be performed for detection bias owing to the small
number of RCTs in the low risk of bias group (n = 2).
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Table 3. Characteristics of randomized controlled trials (RCTs) included in our study (n = 119) associated with high or unclear risk of
bias
Year of
publication
Sample
size
Number of
authors
Language
Funding source
disclosed Affiliationa
Power calculation
includedb
English Chinese Yes No University
Federal/
State Yes No
Selection bias (sequence generation)
Univariate
OR (95% CI) 0.79
(0.70, 0.88)
0.99
(0.99, 1.0)
0.85
(0.75, 0.96) REF
2.6
(0.94, 7.2) REF
7.7
(3.0, 19.8) REF
1.6
(0.74, 3.6) REF
2.2
(0.13, 36.7)
0.0001 0.3 0.01
0.07
<0.0001
0.2
0.6
Multivariable
OR (95% CI) 0.83
(0.73, 0.94) REF
5.0
(1.8, 13.8)
p 0.003
0.002
Selection bias (allocation concealment)
Univariate
OR (95% CI) 0.90
(0.77, 1.1)
0.99
(0.99, 1.0)
0.85
(0.75, 0.96) REF
7.4
(1.9, 29.0) REF
4.0
(1.1, 14.9) REF
1.1
(0.29, 4.2) REF
11.4
(0.66, 197.6)
p 0.2 0.1 0.01
0.004
0.04
0.9
0.09
Multivariable
OR (95% CI)
0.85
(0.75, 0.96)
p
0.01
Performance bias
Univariate
OR (95% CI) 0.87
(0.75, 1.0)
0.99
(0.99, 1.0)
0.83
(0.73, 0.95) REF
7.9
(2.1, 28.5) REF
4.1
(1.2, 14.0) REF
1.2
(0.36, 4.0) REF
51.2
(1.2, 2224.3)
p 0.08 0.2 0.007
0.002
0.02
0.8
0.04
Multivariable
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OR (95% CI)
0.83
(0.73, 0.95)
p
0.007
Attrition bias
Univariate
OR (95% CI) 0.83
(0.74, 0.93)
1.0
(0.99, 1.0)
0.68
(0.56, 0.82) REF
2.7
(0.96, 7.7) REF
3.1
(1.2, 7.6) REF
1.5
(0.66, 3.5) REF
15.0
(0.36, 633.8)
p 0.002 0.7 0.0001
0.06
0.02
0.3
0.2
Multivariable
OR (95% CI)
0.68
(0.56, 0.82)
p
0.0001
Reporting bias
Univariate
OR (95% CI) 0.91
(0.83, 1.0)
0.99
(0.99, 1.0)
0.86
(0.76, 0.98) REF
4.9
(1.5, 16.0) REF
3.5 (1.4,
8.9) REF
2.7
(1.3, 5.8) REF
5.8
(0.14, 243.8)
p 0.06 0.3 0.03
0.008
0.008
0.01
0.4
Multivariable
OR (95% CI)
REF
4.1
(1.2, 13.6) REF
3.0
(1.1, 7.7)
p
0.02
0.03 a
Two RCTs written by authors affiliated with the State and a University were considered part of the University for this analysis. bLogistic regression analysis for detection bias was not performed owing to the small number of RCTs that included power calculation
(n = 2).
Abbreviations: OR = odds ratio; CI = confidence interval.
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Adherence to CONSORT standards for TCM
Rates of adherence to CONSORT standards for TCM are shown in Table 4. Most of the RCTs
(98%) stated the objective adequately. However, most RCTs (94%) did not include the
recommended information (specification of interventions, name of disease, and study design) in
the title or abstract. In the introduction sections, more than half (61%) did not provide the three
names of the compound formulation (Chinese, Latin, and English) as recommended by the
World Health Organization. The methods sections of most RCTs were poorly reported (Table 4).
Most RCTs (ranging from 85% to 98%) failed to describe in enough detail the interventions, type
of study design, calculation of sample size, or methods of randomization and blinding. In the
results sections, many RCTs (78%) did not indicate how participants moved through the study
over time or provide a flow diagram as recommended, and 93% of RCTs did not include
intention-to-treat analysis. The discussion sections were compromised in 8 to 83% of the RCTs
owing to a lack of general interpretation of the results and conflict of interest information.
Table 4. Percentage of randomized controlled trials in our analysis (n = 119) not adherent to
reporting standards provided in the Consolidated Standards of Reporting Trials (CONSORT)
statement for traditional Chinese medicine.
CONSORT item
CONSORT
item no. No. (%)
Title and abstract 1 112 (94)
Introduction
Background 2 73 (61)
Objectives 3 2 (2)
Methods
Participants 4 45 (38)
Interventions 5 101 (85)
Outcomes 6 15 (13)
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Type of study design 7 117 (98)
Sample size 8 117 (98)
Randomization
Sequence generation 9 72 (61)
Allocation concealment 10 109 (92)
Implementation 11 111 (93)
Blinding (masking) 12 107 (90)
Statistical methods 13 48 (40)
Results
Participant flow 14 93 (78)
Recruitment 15 33 (28)
Baseline data 16 31 (26)
Numbers analyzed 17 111 (93)
Outcomes and estimation 18 11 (9)
Ancillary analyses 19 23 (19)
Adverse events 20 40 (34)
Discussion
Interpretation 21 9 (8)
Generalizability 22 14 (12)
Overall evidence 23 99 (83)
Additional analyses
When comparing the risk of bias from the 90 RCTs published before the Cochrane risk of bias
tool was released in 2008 (year of publication 2000-2008) with that of the 29 RCTs published
later, we observed improvement in RCTs published after 2008 in the following domains:
selection bias (22% compared with 59%, p = 0.0004), attrition bias (18% compared with 52%, p
= 0.0005), and reporting bias (41% compared with 66%, p = 0.02). When comparing adherence
to reporting guidelines from the 80 RCTs published before the CONSORT-TCM statement was
released in 2007 (publication date 2000-2007) with that of the 39 RCTs published later, we
observed improvement in RCTs published after 2007 in most of the items except in reporting
sufficient details about the objectives of the study, design, power calculation, and methods to
avoid bias (data not shown). We also evaluated determinants associated with high risk of bias,
compared with unclear risk of bias. In most domains there were no differences. We observed
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differences in allocation concealment, but the characteristics associated with high risk of bias
were the same as those observed with the main comparison high/unclear versus low risk of bias.
There were some characteristics not observed in the main comparison associated with detection
bias (Supplementary Table 3).
DISCUSSION
Our results indicate that serious methodology and reporting flaws still exist in clinical trials
evaluating the effect of CHM in RA. We found that the potential for selection bias was high;
two-thirds of the RCTs in our analysis lacked sufficient detail on how the random sequence was
generated. Similarly, most RCTs were not blinded (e.g., for participants, personnel, or outcome
assessment), thus increasing the potential for both performance and detection bias. Risk of
attrition bias was high or unclear in more than two-third of the RCTs. Reporting bias was also
judged to be high or unclear in half of the included RCTs owing to a lack of study protocol
and/or reporting less than the minimum number of outcome measures recommended to be
included in RA clinical trials.[150] Furthermore, we found that RCTs that were older, had fewer
authors, did not report or disclose funding, were published in a language other than English, or
were written by authors from non-academic settings, were likely to have a high or unclear risk of
bias methodology in at least one of the evaluated domains.
We also found that adherence to reporting standards remains a concern. Title and
abstract, introduction, and methods were even more problematic. Because of these weaknesses,
readers are not provided with clear and transparent information on the interventions or methods
to assess bias in selecting, masking, and evaluating participants. Other areas of concern were
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lack of appropriate general interpretation of the results in the context of current evidence and
incomplete descriptions of conflicts of interest.
It is important to differentiate between the two main concepts reported in this review:
methodological quality and quality of reporting. One of the main components of evidence-based
medicine is the use of available literature to improve decision-making. Stronger inferences can
be drawn from studies in which measures have been taken before, during, and after the
intervention to prevent random and systematic bias. Although RCTs are ranked high in the
hierarchy of evidence, not all RCTs share the same quality, which can lead to biased results.
Quality of reporting is a separate concern. A lack of complete and transparent reporting of the
processes and findings of an RCT is commonly linked to methodological flaws. Poor reporting
leaves out critical information needed to judge study safeguards against bias.
A few systematic reviews evaluating the efficacy of CHM and reporting on the
methodological quality of the studies have shown similar results. However, none of these studies
evaluated CHMs exclusively (i.e., excluding other TCM) in patients with RA. Nonetheless, a
review evaluating the characteristics of 89 studies published between 2000 and 2003 and indexed
in the CNKI reported a lack of unified diagnostic and evaluating standards.[151] Another review
evaluating 20 RCTs published between 2000 and 2010 showed that methodological quality
according to the Jadad scale was generally low, with an average quality score of 1.2 out of
5.[152] Contrastingly, a Cochrane review evaluating herbal medicines in general (including 3
CHMs) showed that the quality of the studies has improved since 2000, but the risk of bias
across different domains was variable.[153] Furthermore, an overview of 31 reviews published
between 1999 and 2009 evaluating several TCM approaches (including CHMs) for multiple
diseases showed that methodological quality improved over the years, although many issues
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remained, specifically a high risk of selection (inadequate randomization methods), attrition
(small sample sizes and high withdrawal rates), and reporting (selective reporting of outcomes)
biases.[154]
To the best of our knowledge, the current study is the first appraising both
methodological quality and adherence to reporting standards specifically in RCTs evaluating
CHM in patients with RA. No other studies have analyzed the characteristics associated with a
high risk of bias or poor adherence to reporting standards. For methodological quality, we used
the risk of bias tool, an instrument endorsed by the Cochrane Collaboration to facilitate improved
appraisal of evidence. The tool has shown significant correlations with other appraisal tools.[155,
156] For example, the risk of bias tool was shown to accurately identify trials that may have
overestimated treatment effects. Studies shown to have a high or unclear risk of bias according to
the risk of bias tool have larger effect estimates than studies shown to have a low risk of bias.[22]
Our study has certain limitations. First, as with any systematic review, it was constrained
by the available data. For example, a protocol or trial registration was not found for most of the
RCTs included in our review. This is concerning because the validity of the conclusion of an
RCT is largely based on adherence to prespecified methods (including outcomes of interest).
Trial registration could improve transparency and help identify gaps in knowledge, prevent
unnecessary duplication in clinical trials, and improve adherence to international quality
standards.[157] Second, we included studies with substantial variation in characteristics (e.g.,
RA diagnosis, TCM syndromes, and CHM descriptions). However, this allowed us to evaluate a
larger number of RCTs. Third, we did not search the CNKI, Chinese Medical Current Contents
(CMCC), and Wanfang Data databases, which could have increased the number of publications
included in this review, because they are not widely available outside Asia, and we felt that there
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was no clear reason to consider that the quality of these studies would have been better.[158]
Lastly, independent quality assessment for non-English language articles could not be performed.
Only one reviewer could translate Chinese articles; therefore, more than 85% of the studies were
evaluated by the translator and cross-checked by another reviewer using the translation from the
first reviewer.
In summary, our results indicate that trials of CHM for the treatment of RA often fail to
meet expected methodological criteria, and high-quality evidence is lacking. Because clinical
trials are just below systematic reviews in the hierarchy of evidence and are used to endorse
recommendations by health organizations, more attention is needed to improve the
methodological robustness of these studies. Future clinical trials evaluating CHMs in RA should
be designed, conducted, and reported according to current specifications and principles.
ACKNOWLEDGMENTS
We are grateful to Yimin Geng from the Research Medical Library of The University of Texas
MD Anderson Cancer Center for helping with the terms included in the search strategies for the
electronic databases and to Ms. Pratibha Nayak for her contributions during the selection of the
studies.
AUTHOR CONTRIBUTIONS
Dr Suarez-Almazor had full access to all of the data in the study and takes responsibility for the
integrity and the accuracy of the data analysis.
Study concept and design: Suarez-Almazor, Lopez-Olivo
Search strategy: Pratt, Geng
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Selection of the studies: Pan, Nayak, Lopez-Olivo
Quality appraisal and data extraction: Pan, Lopez-Olivo
Analysis and interpretation of data: Song, Pan, Lopez-Olivo, Suarez-Almazor
Drafting of the manuscript: Pan, Lopez-Olivo, Song, Suarez-Almazor
Critical revision of the manuscript for important intellectual content: Pan, Lopez-Olivo,
Song, Pratt, Suarez-Almazor
Administrative, technical, or material support: Suarez-Almazor
Study supervision: Suarez-Almazor
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FIGURE LEGENDS
Figure 1. Flow chart of included studies. Abbreviations: RA = rheumatoid arthritis; CHM =
Chinese herbal medicine.
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107. Li JC, Zhao DR. [Treatment of refractory rheumatoid arthritis with integrated Chinese and
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Traditional and Western Medicine [zhong Guo Zhong Xi Yi Jie He za Zhi] 2003; (12).
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00976205/frame.html.
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Figure 1. Flow chart of included studies. Figure 1
203x213mm (300 x 300 DPI)
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Appendix 1. Medline search strategy
Database(s): Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations and Ovid
MEDLINE(R), 1946 to June 2015
No. Search terms
1 RHEUMATOID ARTHRITIS/
2 ((rheumatoid or reumatoid) adj3 (arthriti* or artriti*)).mp.
3 ra.ti.
4 (rheumatism* or rheumarthriti * or antirheumatic* or anti-rheumatic*).ti,ab.
5 ((rheumatic or reumatic) adj3 (arthriti* or polyarthriti*)).ti,ab.
6 rheumat*.jw.
7 or/1-6
8 exp MEDICINE, CHINESE TRADITIONAL/
9 DRUGS, CHINESE HERBAL/
10 TCM.ti.
11 ((China* or Chinese*) adj3 (medicin* or traditional* or natural* or patent*)).mp.
12 ((China* or Chinese*) adj5 herb* adj5 (drug* or prepar* or formula* or pharmac* or
prescri* or mixture* or drink*)).mp.
13 ((China* or Chinese*) adj5 (decoct* or extract* or remedy or remedies or soup* or
infusion*)).mp.
14 ((China* or Chinese*) adj5 (ethnopharm* or phytotherap* or phytomedicin* or
ethnobotanical*)).mp.
15 "Chinese materia medica*".mp.
16 ("zhong yao" or "zhong yi" or "zhongyao" or "zhongyi").mp.
17 or/8-16
18 7 and 17
19 PLANTS, MEDICINAL/
20 ETHNOPHARMACOLOGY/
21 exp PHYTOTHERAPY/
22 exp PLANT PREPARATIONS/
23 exp PLANT ROOTS/
24 plant extracts.rn.
25 or/19-24
26 (China* or Chinese* or "Hong Kong*" or Sino* or Taiwan*).mp.
27 chinese.lg.
28 (China* or Chinese* or "Hong Kong*" or Sino* or Taiwan*).in.
29 (China* or Chinese* or "Hong Kong*" or Taiwan*).jw.
30 (China* or Chinese* or "Hong Kong*" or Taiwan*).cp.
31 or/26-30
32 25 and 31
33 7 and 32
34 TRIPTERYGIUM/
35 ("Tripterygi* wilfordi*" or "thunder god vine*" or "Lei Gong Teng" or LeiGongTeng or
triptolide or celastrol).mp.
36 exp PAEONIA/
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37 (peony* or paeonia* or "Bai Shao" or BaiShao).mp.
38 SAUSSUREA/
39 (Xuelian or Xue Lian or Saussurea).mp.
40 SINOMENIUM/
41 (Zheng Qing Feng Tong Ning or ZhengQing FengTongNing or Sinomeni*).mp.
42 or/34-41
43 7 and 42
44 Tripterygi* Hypoglauc*.mp.
45 Aconit* Kusnezofi*.mp.
46 Aconit* Carmichael*.mp.
47 Cyathul*.mp.
48 Clematid*.mp.
49 Rehmanni*.mp.
50 Spatholob*.mp.
51 Seolopendr*.mp.
52 Scorpio*.mp.
53 Stephani*.mp.
54 Ephedr*.mp.
55 Glycyrrhiz*.mp.
56 Angelic* Sinensi*.mp.
57 Gentian* Macrophyll*.mp.
58 Astragal*.mp.
59 Asari*.mp.
60 Notopterygi*.mp.
61 (Chuanxiong* or Chuan xiong*).mp.
62 Saposhnikovi*.mp.
63 Angelic* Pubescent*.mp.
64 Lateral* Praeparat*.mp.
65 Cinnamom*.mp.
66 Anemarrhen*.mp.
67 Paeoni* Alba*.mp.
68 Terminali*.mp.
69 Cartham*.mp.
70 or/44-69
71 7 and 70
72 (San Zi Yang Qin* or SanZiYangQin*).mp.
73 (Huo Luo Xiao Ling* or HuoLuoXiaoLing*).mp.
74 (Yi Wei* or YiWei*).mp.
75 (Sheng Yang Yi Wei* or ShengYangYiWei*).mp.
76 (San Miao Wan* or SanMiaoWan*).mp.
77 (Si Ni* or SiNi).mp.
78 (Dang Gui Si Ni* or DangGuiSiNi*).mp.
79 (Wu Tou* or WuTou*).mp.
80 (Shen Tong Zhu Yu* or ShenTongZhuYu*).mp.
81 (Huang Qi Gui Zhi Wu Wu* or Huang QiGuiZhiWuWu*).mp.
82 (Bai Hu Jia Gui Zhi* or BaiHuJiaGuiZhi*).mp.
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83 (Xuan Bi* or XuanBi*).mp.
84 (Du Huo Ji Sheng* or DuHuoJiSheng*).mp.
85 (Si Wu* or SiWu*).mp.
86 (Tao Hong si Wu* or TaoHongSiWu*).mp.
87 (Gui Zhi* or GuiZhi*).mp.
88 (Juan Bi* or JuanBi*).mp.
89 (Xiao Huo Luo* or XiaoHuoLuo*).mp.
90 (Ma Huang Fu Zi Gan Cao* or MaHuangFuZiGanCao*).mp.
91 (Fu Zi* or FuZi).mp.
92 (Fang Feng* or FangFeng*).mp.
93 (Yi Yi Ren* or YiYiRen*).mp.
94 (Si Jun Zi* or SiJunZi*).mp.
95 (Xiao Jian Zhong* or XiaoJianZhong*).mp.
96 (Huang Qi Jian Zhong* or HuangQiJianZhong*).mp.
97 (San Bi* or SanBi).mp.
98 (Yang He* or YangHe*).mp.
99 (Ren Shen Yang Rong* or RenShenYangRong*).mp.
100 (Bai Hu* or BaiHu).mp.
101 (Qing Ying* or QingYing*).mp.
102 (Tong Xie Yao Fang* or TongXieYaoFang*).mp.
103 (Xue Fu Zhu Yu* or XueFuZhuYu*).mp.
104 or/72-103
105 7 and 104
106 (Chuan Xiong Qin* or ChuanXiongQin*).mp.
107 (Huang Qi* or HuangQi*).mp.
108 (Shi Re Bi* or ShiReBi*).mp.
109 (Zhuang Gu* or ZhuangGu*).mp.
110 (Pan Long Qi* or PanLongQi*).mp.
111 (Kun Ming Shan Hai Tang* or KunMingShanHaiTang*).mp.
112 (Zheng Qing Feng Tong Ning* or ZhengQingFengTongNing*).mp.
113 (Yu Xue Bi* or YuXueBi*).mp.
114 (Han Shi Bi* or HanShiBi*).mp.
115 (Lei Gong Teng* or LeiGongTeng*).mp.
116 (Lei Gong Teng Duo Dai* or LeiGongTengDuoDai*).mp.
117 (Huo Luo* or HuoLuo*).mp.
118 (Bao An Wan Ling* or BaoAnWanLing*).mp.
119 (Shou Feng Shun Qi* or ShouFengShunQi*).mp.
120 (Feng Shi* or FengShi*).mp.
121 (Gu Ci Xiao Tong* or GuCiXiaoTong*).mp.
122 (Fu Fang Xia Tian Wu* or FuFangXiaTianWu*).mp.
123 (Xia Tian Wu* or XiaTianWu*).mp.
124 (Er Xian* or ErXian*).mp.
125 (Zhui Feng Tou Gu* or ZhuiFengTouGu*).mp.
126 (Hong Hua* or HongHua*).mp.
127 (She Xiang Zhui Feng* or SheXiangZhuiFeng*).mp.
128 (Zhui Feng* or ZhuiFeng*).mp.
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129 (Shen Jin Huo Luo* or ShenJinHuoLuo*).mp.
130 (Xiao Huo Luo* or XiaoHuoLuo*).mp.
131 or/106-130
132 7 and 131
133 (zushima* or zu shi ma*).mp.
134 (biqi* or bi qi*).mp.
135 (wangbi* or wang bi*).mp.
136 Yishen Juanbi*.mp.
137 Yi shen Juan bi*.mp.
138 Shiguogong*.mp.
139 Shi guo gong*.mp.
140 Yunnan Baiyao*.mp.
141 Yun nan Bai yao*.mp.
142 Daphne*.mp.
143 Feng Shi*.mp.
144 FengShi*.mp.
145 or/133-144
146 7 and 145
147 18 or 33 or 43 or 71 or 105 or 132 or 146
148 (animals not (humans and animals)).sh.
149 147 not 148
150 (case reports not (case reports and review)).pt.
151 case report*.ti. not review.pt.
152 150 or 151
153 149 not 152
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Supplementary Figure 1. Risk of bias across randomized controlled trials included in our
analysis (n = 119), evaluated using the Cochrane risk of bias assessment tool.[20]
0% 20% 40% 60% 80% 100%
Other bias
Reporting bias
Attrition bias
Detection bias
Performance bias
Selection bias (allocation concealment)
Selection bias (sequence generation)
Low Unclear High
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Supplementary Table 1. Characteristics of each included study.
Study, year [ref] Year Language Country Centers Intervention
arms
Sample
size
Eligibility criteria Affiliation
Chen 2013 [24] 2013 EN China 1 3 1784 ACR RA University
Chen 2013 [25] 2013 EN China 3 2 194 ACR RA University
Chen 2010 [26] 2010 CHN China 1 2 90 ACR RA State
Du 2005 [27] 2005 CHN China 1 2 61 ACR RA State
Fan 2007 [28] 2007 CHN China 1 2 96 ACR RA+TCM guideline (≥3) State
Goldbach-Mansky
2009 [29] 2009 EN US
11 2 121 ACR RA Federal
He 2008 [30] 2014 CHN China 1 2 46 ACR RA University
Ji 2002 [31] 2002 EN China 1 2 82 ACR RA State
Jiang 2012 [32] 2012 EN China 1 2 86 ACR RA University
Jiao 2012 [33] 2012 CHN China 1 2 67 ACR RA+TCM guideline (1) Federal
Jie 2012 [34] 2012 CHN China 2 3 138 ACR RA+TCM guideline (1) University
Kang 2010 [35] 2010 CHN China 1 2 38 ACR RA+TCM guideline (1) University
Li 2007 [36] 2007 EN China-Hong
Kong 1 2 65
ACR RA University
Li 2002 [37] 2002 CHN China 1 2 30 ACR RA University
Li 2006 [38] 2006 CHN China 1 2 120 ACR RA State
Liang 2000 [39] 2000 CHN China 1 2 96 ACR RA+TCM guideline (1) State
Lin 2011 [40] 2011 CHN China 5 3 240 ACR RA University
Liu 2008 [41] 2008 CHN China 1 2 90 ACR RA+TCM guideline (1) State
Liu 2006 [42] 2006 CHN China 1 3 40 ACR RA University
Liu 2006 [43] 2006 CHN China 1 2 120 ACR RA University
Liu 2007 [44] 2007 CHN China 1 2 120 ACR RA+TCM guideline (1) University
Liu 2006 [45] 2006 CHN China 1 2 142 ACR RA+TCM guideline (2) University
Liu 2009 [46] 2009 CHN China 1 2 100 ACR RA+TCM guideline (1) State
Lu 2002 [47] 2002 CHN China 1 2 60 ACR RA State
Shen 2011 [48] 2011 EN China 1 2 80 ACR RA+TCM guideline (1) University
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Shen 2003 [49] 2003 EN China 1 2 106 ACR RA State(City)
Song 2007 [50] 2007 EN Korea 7 2 183 ACR RA University
Tao 2002 [51] 2002 EN China 1 3 35 ACR RA Federal
Wang 2013 [52] 2013 CHN China 1 2 240 ACR RA+TCM guideline (1) Federal
Wu 2001 [53] 2001 CHN China 1 2 70 ACR RA State
Yang 2003 [54] 2003 EN China 1 2 60 ACR RA+TCM guideline (1) State
Yu 2007 [55] 2007 CHN China 1 3 70 ACR RA+TCM guideline (≥3) State
Yu 2013 [56] 2013 CHN China 1 3 230 ACR RA+TCM guideline (1) State(City)
Yu 2005 [57] 2005 EN China 1 2 90 ACR RA University
Zhang 2007 [58] 2007 CHN China 1 2 84 ACR RA State
Zhao 2012 [59] 2012 CHN China 1 2 104 ACR RA University
Zhao 2006 [60] 2006 CHN China 1 2 80 ACR RA University
Zhou 2009 [61] 2009 CHN China 1 2 78 ACR RA+TCM guideline (1) Federal
Zhou 2010 [62] 2010 CHN China 1 2 120 ACR RA+TCM guideline (1) Federal
Zhou 2002 [63] 2002 CHN China 1 2 170 ACR RA+TCM guideline (1) State(City)
Zhou 2006 [64] 2006 CHN China 1 2 80 ACR RA University
Zhou 2000 [65] 2000 EN China 1 3 128 ACR RA+TCM guideline (2) University
Zhou 2004 [66] 2004 EN China 1 2 118 ACR RA+TCM guideline (1) University
Zhang 2006 [67] 2006 CHN China 1 2 150 ACR RA University
Zuo 2009 [68] 2009 CHN China 1 2 78 ACR RA University
Sun 2002 [69] 2002 EN China 1 2 76 ACR RA State(City)
Li 2013 [70] 2013 CHN China 1 2 118 ACR RA+TCM guideline (1) University
Hang 2005 [71] 2005 CHN China 6 2 240
ACR RA+TCM Sx_no
guidelines
State(City) and
University
Xun 2010 [72] 2010 CHN China 1 2 86 ACR RA+TCM guideline (1) University
Ding 2010 [73] 2010 CHN China 1 2 63 ACR RA State(City)
Tang 2002 [74] 2002 CHN China 1 2 91 ACR RA Federal
Tu 2006 [75] 2006 CHN China 1 2 80 ACR RA University
Guo 2003 [76] 2003 CHN China 1 3 328 ACR RA Federal
Chen 2005 [77] 2005 CHN China 1 2 44 ACR RA State(City)
Guan 2005 [78] 2005 CHN China 1 2 80 ACR RA University
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Ma 2008 [79] 2008 CHN China 1 2 189
ACR RA+TCM Sx_no
guidelines State(City)
Hu 2007 [80] 2007 CHN China 1 2 74 ACR RA State(City)
Li 2003 [81] 2003 CHN China 1 2 60 ACR RA University
Liu 2000 [82] 2000 CHN China 1 2 80 ACR RA State(City)
Wang 2001 [83] 2001 CHN China 1 2 322
ACR RA+TCM Sx_no
guidelines State(City)
Xiao 2008 [84] 2008 CHN China 1 2 96 ACR RA State(City)
Zou 2007 [85] 2007 CHN China 1 2 60
ACR RA+TCM guideline
(unspecified #) State(City)
Wang 2006 [86] 2006 CHN China 1 2 60 ACR RA State(City)
Ma 2002 [87] 2002 CHN China 1 2 360 ACR RA+TCM guideline (≥3) State(City)
Wu 2004 [88] 2004 CHN China 1 2 86
ACR RA+TCM Sx_no
guidelines University
Jiang 2000 [89] 2000 CHN China 1 2 280 ACR RA State(City)
Liang 2000 [90] 2000 CHN China 1 2 66 ACR RA State
Tao 2002 [91] 2002 CHN China 1 2 70 ACR RA State(City)
Lv 2000 [92] 2000 CHN China 1 2 72 ACR RA University
Zhang 2005 [93] 2005 CHN China 1 2 80 ACR RA+TCM guideline (1) State(City)
Chen 2005 [94] 2005 CHN China 1 2 82 ACR RA University
Xiao 2008 [95] 2008 CHN China 1 2 110 ACR RA State(City)
Huang 2007 [96] 2007 CHN China 1 2 196 ACR RA University
Fan 2000 [97] 2000 CHN China 1 2 129 ACR RA State(City)
Zhen 2006 [98] 2006 CHN China 1 2 50 ACR RA+TCM guideline (1) State(City)
Ji 2008 [99] 2008 CHN China 1 2 101 ACR RA State(City)
Xu 2005 [100] 2005 CHN China 1 2 200
ACR RA+TCM Sx_no
guidelines State(City)
Wang 2006 [101] 2006 CHN China 1 3 150 ACR RA State(City)
Liu 2007 [102] 2007 CHN China 1 2 52 ACR RA State(City)
He 2001 [103] 2001 CHN China 1 2 62 ACR RA+TCM guideline (2) State(City)
Liu 2003 [104] 2003 CHN China 1 2 3789
ACR RA+TCM Sx_no
guidelines State(City)
Huang 2002 [105] 2002 CHN China 1 2 59 ACR RA State(City)
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Li 2001 [106] 2001 CHN China 1 2 78 ACR RA State
Li 2003 [107] 2003 CHN China 1 2 160
ACR RA+TCM guideline
(unspecified #) Rural
Xin 2005 [108] 2005 CHN China 1 2 90 ACR RA State(City)
Leng 2000 [109] 2000 CHN China 1 2 80 ACR RA University
Wang 2005 [110] 2005 CHN China 1 2 168 ACR RA State(City)
Zeng 2006 [111] 2006 CHN China 1 2 70 ACR RA State(City)
Ji 2007 [112] 2007 CHN China 1 2 80 ACR RA State(City)
Cai 2006 [113] 2006 CHN China 1 2 90
ACR RA+TCM Sx_no
guidelines State(City)
Wu 2004 [114] 2004 CHN China 1 2 56 ACR RA University
Guo 2003 [115] 2003 CHN China 1 2 200 ACR RA State(City)
Li 2008 [116] 2008 CHN China 1 2 60
ACR RA+TCM Sx_no
guidelines State
Chen 2007 [117] 2007 CHN China 1 2 140 ACR RA State(City)
Li 2003 [118] 2003 CHN China 1 2 57 ACR RA+TCM guideline (≥3) State(City)
Du 2003 [119] 2003 CHN China 1 2 80 ACR RA State(City)
Xu 2004 [120] 2004 CHN China 1 2 63 ACR RA State
Shi 2007 [121] 2007 CHN China 1 2 88 ACR RA State(City)
Hui 2008 [122] 2008 CHN China 1 2 60 ACR RA State
Meng 2006 [123] 2006 CHN China 1 2 60 ACR RA State
Wang 2004 [124] 2004 CHN China 1 2 122
ACR RA+TCM Sx_no
guidelines State(City)
He 2014 [125] 2014 CHN China 1 2 88 ACR RA+TCM guideline (1) State
Huang 2013 [126] 2014 EN China 1 2 300 ACR RA University
Kou 2013 [127] 2014 EN China 9 2 489 ACR RA+TCM guideline (≥3)
State and
University
Liu 2014 [128] 2013 CHN China 4 2 212 ACR RA+TCM guideline (1) Federal
Wang 2014 [129] 2013 CHN China 1 2 80
ACR RA+TCM guideline
(unspecified #) University
Guo 2008 [130] 2008 CHN China 1 2 50 ACR RA University
Tao 2011 [131] 2011 CHN China 1 2 105 ACR RA Federal
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Zhu 2011 [132] 2011 CHN China 1 2 41 ACR RA University
Zheng 2009 [133] 2009 CHN China 2 2 102 ACR RA+TCM guideline (1) University
Liu 2003 [134] 2003 CHN China 1 2 40 ACR RA University
Sun 2003 [135] 2003 CHN China 1 2 60 ACR RA+TCM guideline (1) University
Cui 2004 [136] 2004 CHN China 1 2 108 ACR RA State(City)
Liu 2008 [137] 2008 CHN China 5 2 439 ACR RA+TCM guideline (1) State
Ao 2005 [138] 2005 CHN China 1 2 60 ACR RA+TCM guideline (1) University
Wu 2001 [139] 2001 CHN China 1 2 70 ACR RA State
Wang 2007 [140] 2007 CHN China 1 2 62 ACR RA State(City)
He 2002 [141] 2002 CHN China 1 2 83
ACR RA+TCM Sx_no
guidelines State
Lv 2014 [142] 2014 EN China 9 3 207 ACR RA University
ACR RA=American College of Rheumatology Classification Criteria for rheumatoid arthritis; CHN=Chinese; ENG=English;
TMC=Traditional Chinese Medicine; Sx=Syndrome
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Supplementary Table 2. Characteristics of randomized controlled trials (RCTs) included in our analysis (n = 119) according to risk
of bias.a
Characteri
stic
Selection bias
(random sequence)
Selection bias
(allocation
concealment) Performance bias Detection bias Attrition bias Reporting bias High/
unclear, n
= 82
Low,
n =
37 p
High/
unclear,
n = 109
Low,
n =
10 p
High/
unclear,
n = 107
Low,
n =
12 p
High/
unclear,
n = 117
Low,
n = 2 p
High/
unclear,
n = 88
Low
, n =
31 p
High/
unclear,
n = 63
Low,
n =
56 p
Mean year
of
publication
±SD
2005 ±
3.6
2008.5
± 3.7 <0.0001
2006 ±
3.8
2007.
7 ±
4.6
0.3 2006 ±
3.8
2008 ±
4.2 0.09
2006 ±
3.9
2011
± 4.2 0.09 2005.5
± 3.6
2008 ±
4.2 0.003 2005.6
± 3.6
2007±
4.1 0.1
Mean
sample size
± SD
130.5 ±
197.4
222.1
±
610.8
0.6 111.4 ±
73.2
677
±
1215.
4
0.3 141.8 ±
361.8
312.1 ±
487.3 0.3
156.2 ±
379.7
323 ±
164.1 0.04
166.4 ±
435.2
138.0
±
100.6
0.1 113.7 ±
78.5
209.9
±
541.8
0.9
Mean no.
of authors
± SD
3.7 ±
2.6
6.1 ±
6.0 0.007
4.0 ±
3.6
8.9 ±
6.1 0.002
4.0 ±
3.6
8.8 ±
5.9 0.0008
4.2 ±
3.2
18.5
±
19.1
0.09 3.4 ±
2.0
7.5 ±
6.4 <0.0001
3.6 ±
4.1
5.4 ±
3.9 0.0004
Mean
Impact
Factor ±
SD
0.48 ±
0.45
1.8 ±
3.2 <0.0001
0.62 ±
0.95
4.0 ±
5.2 0.0005
0.60 ±
0.94
3.6 ±
4.8 0.0002
0.83 ±
1.8
4.8 ±
6.4 0.5
0.50 ±
0.45
2.0 ±
3.5 <0.0001
0.55 ±
1.2
1.3 ±
2.5 <0.0001
No. of non-
English
language
(%)
73 (89) 28
(75.7) 0.06
96
(88.1)
5
(50) 0.007
95
(88.8) 6 (50) 0.003
100
(85.5)
1
(50) 0.3
78
(88.6)
23
(74.2) 0.08
59
(93.7)
42
(75) 0.005
No. of
RCTs with
no source
73 (89) 19
(51.4) <0.0001
87
(79.8)
5
(50) 0.05
86
(80.4) 6 (50) 0.03
91
(77.8)
1
(50) 0.4 73 (83)
19
(61.3) 0.01
55
(87.3)
37
(66.1) 0.006
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of funding
listed (%)
No. non-
academic
RCTs (%)
54
(65.9)
20
(54.1) 0.2
68
(62.4)
6
(60) 1
67
(62.6) 7 (58.3) 0.8
73
(62.4)
1
(50) 1
57
(64.8)
17
(54.8) 0.3 46 (73)
28
(50) 0.01
No. of
RCTs with
no power
calculation
provided
(%)
81
(98.8)
36
(97.3) 0.5
108
(99.1)
9
(90) 0.2
107
(100)
10
(83.3) 0.009
115
(98.3)
2
(100) 1
88
(100)
29
(93.5) 0.07
63
(100)
54
(96.4) 0.2
aRCTs judged to have an unclear risk of bias were merged with those judged to have a high risk of bias. bEither Impact Factor (2013) or the China National Knowledge Infrastructure database was used. cTwo RCTs written by authors affiliated with the State and a University were part of the University for this analysis
Abbreviations: SD = standard deviation.
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Supplementary Table 3. Characteristics of randomized controlled trials (RCTs) included in our analysis according to comparison of
high risk vs. unclear
Characteristic
Selection bias
(random sequence)
Selection bias
(allocation
concealment) Performance bias Detection bias Attrition bias Reporting bias
High,
n =13
Unclear,
n = 69 p
High,
n = 36 Unclear,
n=73 P
High,
n = 101 Unclear, n = 6 p
High,
n = 106 Unclear,
n =11 p
High,
n = 5 Unclear,
n = 83 p
High,
n = 48 Unclear,
n=15 p
Mean year of
publication
±SD
2005 ±
3.5
2005.2
± 3.6
0.9 2007.2
± 4.06
2005.
6 ±
3.6
0.05 2006.1
± 3.9
2005.3
± 3.0
0.8 2005.9
± 3.8
2008.2
± 4.4
0.1 2008.4
± 4.5
2005.4 ±
3.5
0.1 2005.1
± 3.6
2007.1
± 3.2 0.05
Mean sample
size ± SD
101.4 ±
36.1
136.0 ±
214.5
0.7 109.7 ±
51.6
112.3
±
82.0
0.2 143.6 ±
372.3
109.2 ±
46.6
0.5 141.2 ±
363.5
300.6 ±
509.4
0.5 115.6 ±
46.9
169.4 ±
448.0
0.3 107.6 ±
71
133.4
± 99.1
0.3
Mean no. of
authors ± SD
4.2 ±
2.3
3.6 ±
2.7
0.3 4.4 ±
1.8
3.9 ±
4.3 0.005 4.0 ±
3.7
3.3 ±
2.0
0.7 3.7 ±
2.3
9.1 ±
6.0
0.00
07
3.4 ±
1.5
3.4 ± 2.0 0.8 3.8 ±
4.6
2.8 ±
1.7
0.4
Mean Impact
Factor ± SD
0.47 ±
0.27
0.48 ±
0.48
0.6 0.83 ±
0.39
0.51
±
1.11
<0.000
1
0.61 ±
0.96
0.45 ±
0.27
0.8 0.51 ±
0.39
3.9 ±
4.9
<0.0
001
1.0 ±
1.0
0.46 ±
0.38
0.2 0.62 ±
1.3
0.33 ±
0.27
0.4
No. of non-
English
language (%)
12
(92.3)
61
(88.4)
1.0 27 (75) 69
(94.5) 0.009 89
(88.1)
6 (100) 1.0 95
(89.6)
5 (45.5) 0.00
1
3 (60) 75 (90.4) 0.1 44
(91.7)
15
(100) 0.6
No. of RCTs
with no source
of funding
listed (%)
12
(92.3)
61
(88.4)
1.0 24
(66.7)
63
(86.3) 0.02 80
(79.2)
6 (100) 0.6 86
(81.1)
5 (45.5) 0.02 5 (100) 68 (81.9) 0.6 41
(85.4)
14
(93.3) 0.4
No. non-
academic RCTs
(%)
8
(61.5)
46
(66.7)
0.8 18 (50) 50
(68.5)
0.06 64
(63.4)
3 (50) 0.7 67
(63.2)
6 (54.5) 0.7 2 (40) 55 (66.3) 0.3 33
(68.8)
13
(86.7) 0.3
No. of RCTs
with no power
calculation
provided (%)
13
(100)
68
(98.6)
1.0 36
(100)
72
(98.6)
1.0 101
(100)
6 (100) - 106
(100)
9 (81.8) 0.00
81
5 (100) 83 (100) - 48
(100)
15
(100)
-
Abbreviations: SD = standard deviation.
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PRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 Checklist
Section/topic # Checklist item Reported on page #
TITLE
Title 1 Identify the report as a systematic review, meta-analysis, or both. 1
ABSTRACT
Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.
4-5
INTRODUCTION
Rationale 3 Describe the rationale for the review in the context of what is already known. 7-8
Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).
8
METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
NA
Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered,
language, publication status) used as criteria for eligibility, giving rationale. 9
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.
8-9
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.
Suppl. File
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
9
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
9-10
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
10
Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
10
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). 11
Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency
(e.g., I2) for each meta-analysis.
11
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PRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 Checklist
Page 1 of 2
Section/topic # Checklist item Reported on page #
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
10
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
11
RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
12 & Figure 1
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
12 & Table 1
Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). 16
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
NA
Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. 17 & Table 3
Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Suppl. Fig.
Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). 22
DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).
23
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).
25
Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. 25
FUNDING
Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.
2
From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(6): e1000097. doi:10.1371/journal.pmed1000097
For more information, visit: www.prisma-statement.org. Page 2 of 2
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Systematic Review of the Methodological Quality of Controlled Trials Evaluating Chinese Herbal Medicine in
Patients with Rheumatoid Arthritis
Journal: BMJ Open
Manuscript ID bmjopen-2016-013242.R2
Article Type: Research
Date Submitted by the Author: 17-Jan-2017
Complete List of Authors: Pan, Xin; Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Department of Rheumatology Lopez-Olivo, M; The University of Texas MD Anderson Cancer Center
Song, Juhee; The University of Texas, MD Anderson Cancer Center, Department of Biostatistics Pratt, Gregory; The University of Texas, MD Anderson Cancer Center, Research Medical Library Suarez-Almazor, Maria; The University of Texas MD Anderson Cancer Center, General Internal Medicine
<b>Primary Subject Heading</b>:
Rheumatology
Secondary Subject Heading: Research methods, Complementary medicine, Evidence based practice, Medical publishing and peer review
Keywords: Chinese herbal medicine, Quality of randomized controlled trials, Traditional Chinese medicine, Systematic review, Rheumatoid arthritis
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1
Systematic Review of the Methodological Quality of Controlled Trials Evaluating Chinese
Herbal Medicine in Patients with Rheumatoid Arthritis
Xin Pan1, Maria A. Lopez-Olivo
2, Juhee Song
3, Gregory Pratt
4, Maria E. Suarez-Almazor
2.
1Department of Rheumatology, Shuguang Hospital, Shanghai University of Traditional Chinese
Medicine, Shanghai, China; 2Department of General Internal Medicine, Rheumatology Section,
3Department of Biostatistics, and
4Research Medical Library, The University of Texas MD
Anderson Cancer Center, Houston, TX 77030, USA.
Corresponding Author: Maria E. Suarez-Almazor, MD, PhD, Department of General Internal
Medicine, Unit 1467, The University of Texas MD Anderson Cancer Center, 1515 Holcombe
Boulevard, Houston, TX 77030, USA. Phone: 713-563-6209. Fax: 713-563-4491. Email:
msalmazor@mdanderson.org.
The Corresponding Author has the right to grant on behalf of all authors and does grant on
behalf of all authors a worldwide licence to the Publishers and its licensees in perpetuity, in all
forms, formats, and media (whether known now or created in the future), to i) publish,
reproduce, distribute, display, and store the Contribution; ii) translate the Contribution into
other languages, create adaptations, create reprints, include the Contribution within collections,
and create summaries, extracts, or abstracts of the Contribution; iii) create any other derivative
work(s) based on the Contribution; iv) exploit all subsidiary rights in the Contribution; v)
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include electronic links from the Contribution in third party material wherever it may be located;
and vi) licence any third party to do any or all of the above.
Word count: 3,708
Number of figures: 1
Number of tables: 4
Number of references: 151
Number of supplementary files: 1
SOURCE OF FUNDING
The statistical analysis in this research (through the Biostatistics Resource Group) was supported
in part by a Cancer Center Support Grant from the National Cancer Institute (P30CA016672) to
The University of Texas MD Anderson Cancer Center.
COMPETING INTERESTS
We have read and understood BMJ Open policy on declaration of interests and declare the
following interests. (1) Dr. Suarez-Almazor is the recipient of a K24 career award from the
National Institute for Musculoskeletal and Skin Disorders. (2) Dr. Pan’s work is supported by the
Shanghai Municipal Education Commission and the Shanghai Shuguang Hospital, Shanghai
University of TCM. (3) Dr. Lopez-Olivo is the recipient of a career award from the
Rheumatology Research Foundation and has received a consulting fee from Complete HEOR
Solutions outside the scope of the submitted work. The authors have no other relationships or
activities that could appear to have influenced the submitted work. In addition, none of the
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authors has had relationships with companies that might have an interest in the submitted work
in the previous 3 years. The authors’ spouses, partners, or children also have no financial
relationships that may be relevant to the submitted work. None of the authors has any
nonfinancial interests that may be relevant to the submitted work. All authors have completed the
Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request
from the corresponding author).
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ABSTRACT
Objectives: We appraised the methodological and reporting quality of randomized controlled
clinical trials (RCTs) evaluating the efficacy and safety of Chinese herbal medicine (CHM) in
patients with rheumatoid arthritis (RA).
Design: For this systematic review, electronic databases were searched from inception until June
2015. The search was limited to humans and non-case report studies, but was not limited by
language, year of publication, or type of publication. Two independent reviewers selected RCTs,
evaluating CHM in RA (herbals and decoctions). Descriptive statistics were used to report on
risk of bias and their adherence to reporting standards. Multivariable logistic regression analysis
was performed to determine study characteristics associated with high or unclear risk of bias.
Results: Out of 2,342 unique citations, we selected 119 RCTs including 18,919 patients: 10,108
patients received CHM alone and 6,550 received 1 of 11 treatment combinations. A high risk of
bias was observed across all domains: 21% had a high risk for selection bias (11% from
sequence generation, 30% from allocation concealment), 85% for performance bias, 89% for
detection bias, 4% for attrition bias, and 40% for reporting bias. In multivariable analysis, fewer
authors was associated with selection bias (allocation concealment), performance bias, and
attrition bias, and earlier year of publication and funding source not reported or disclosed were
associated with selection bias (sequence generation). Studies published in non-English language
were associated with reporting bias. Poor adherence to recommended reporting standards (less
than 60% of the studies not providing sufficient information) was observed in 11 of the 23
sections evaluated.
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Limitations: Study quality and data extraction were performed by one reviewer and cross-
checked by a second reviewer. Translation to English was performed by one reviewer in 85% of
the included studies.
Conclusions: Studies evaluating CHM often fail to meet expected methodological criteria, and
high-quality evidence is lacking.
Keywords: traditional Chinese medicine, Chinese herbal medicine, rheumatoid arthritis,
randomized controlled trial, systematic review
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STRENGTHS OF THIS STUDY
1. First study appraising both methodological quality and adherence to reporting standards
specifically in RCTs evaluating Chinese herbal medicines in patients with rheumatoid
arthritis. No other studies have analyzed the characteristics associated with a high risk of
bias or poor adherence to reporting standards.
2. For methodological quality, we used the risk of bias tool, an instrument endorsed by the
Cochrane Collaboration to facilitate improved appraisal of evidence. The tool has shown
significant correlations with other appraisal tools.
3. For reporting adequacy, we used the CONSORT statement which is a minimum set of
recommendations for reporting randomized trials. It was developed by a team of
international experts and is widely used worldwide and encouraged by the leading
journals for the reporting of trials (over 50% of the core medical journals listed in the
Abridged Index Medicus on PubMed - e.g., BMJ, BMJ Open, New England Journal of
Medicine, Journal of the American Medical Association).
LIMITATIONS OF THIS STUDY
4. We did not search the Chinese Medical databases.
5. More than 85% of the studies were evaluated by the translator and cross-checked by
another reviewer using the translation from the first reviewer.
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INTRODUCTION
Rheumatoid arthritis (RA) is one of the leading causes of disability worldwide, affecting
1% of the world population. According to the Global Burden of Disease 2010 Study, years lived
with disability from RA increased from 2’566,000 in 1990 to 3’776,000 in 2010.[1] With aging
populations throughout the world, and declines in mortality, the number of people living with
RA will increase substantially over coming decades.
Chinese herbal medicines (CHMs) have been used to treat rheumatoid arthritis (RA) for
many years, mostly in Asia. The use of CHMs is generally based on experience and is influenced
by a holistic concept of health.[2] In traditional Chinese medicine (TCM), RA belongs to the
category of “bi syndrome;” i.e., it is believed to be caused by attacks of wind, cold, dampness, or
heat, which cause disharmony between bodily systems.[3, 4] Patients are classified as having a
particular TCM syndrome according to their symptoms and then treated with CHMs to decrease
inflammation by restoring the affected system or to ameliorate the side effects of disease-
modifying antirheumatic drugs.[5] TCM guidelines have been developed by the Chinese
government for the diagnosis and treatment of these syndromes [6-8].
There are numerous CHM preparations for the treatment of RA, including decoctions,
whole plants, plant extracts, and patented formulas,[9-11] all of which can be given as a single
herb or a mixture of herbs.[12] Patented CHMs are often offered as chemical preparations,
tablets, and capsules with simple and convenient dosing schedules and reduced aftertaste.[2, 12]
This has increased the acceptance of CHM in Western countries. In 2002, a national survey
conducted in the United States reported that almost 20% of adults had used herbal therapies in
the past year.[13] In the United Kingdom, a systematic review of 89 surveys on the use of
complementary medicine showed that more than 50% of respondents with a chronic condition
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reported using this type of medicine during their lifetime.[14] Furthermore, the use rate of herbal
therapies in patients with arthritis in US primary care settings has been reported to be as high as
90%.[15]
After the introduction of evidence-based medicine in China, several randomized
controlled trials (RCT) were conducted to evaluate the efficacy of CHMs for RA.[10, 12, 16, 17]
However, the methodology used to conduct these trials was inconsistent, and the results were
conflicting. Quality of reporting is intrinsically linked to the methodological quality of RCTs.
Criteria for standardization facilitate complete and transparent reporting and help to improve
critical appraisal and interpretation of an RCT. Since the development of the Consolidated
Standards of Reporting Trials (CONSORT) statement in 1996, most high-impact journals have
endorsed its use to improve reporting of RCTs.[18] In 2006, the CONSORT extension for
reporting herbal medicines was developed, and in 2007, a draft of the extension for reporting
TCM was released.[19]
To date, no systematic review has explored the study characteristics associated with
methodological quality in controlled trials (randomized or not) evaluating the efficacy,
effectiveness, or safety of CHMs in the treatment of RA. The objectives of our study were to
appraise the methodological quality of these studies by ascertaining potential risk of bias, to
identify publication factors associated with methodological flaws, and to determine the quality of
reporting according to CONSORT recommendations.
METHODS
We report our methods and results according to the Preferred Reporting Items for Systematic
Review and Meta-Analysis statement.
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Information sources
We searched electronic databases (Medline, EMBASE, Cochrane Library, and Web of Science)
from inception through June 2015 for studies evaluating the use of CHM, including herbals or
decoctions (e.g., “tang”), in patients with RA (search terms are listed in Appendix 1). Our search
was restricted to human studies and excluded case reports but was not limited by language, year
of publication, or type of publication. We also searched the reference lists of potentially relevant
citations (controlled trials and reviews, although reviews themselves were later excluded from
the analysis) to identify additional studies that were not published or otherwise found. EndNote
X6 and DistillerSR were used to manage the records retrieved.
Study selection and eligibility criteria
Two reviewers (X.P. and Pratibha Nayak) independently screened the titles and abstracts of all
citations obtained by our searches. They resolved any disagreements through discussion and
consensus. When no consensus was reached, a third party acted as an adjudicator (M.L.-O.). We
included any RCT evaluating the efficacy, effectiveness, or safety of CHMs in adult patients (age
≥18 years) with RA. All types of CHMs were considered: (i) patented medicines (pharmaceutical
preparation or formulations) made from herbs (e.g., tablets, liquids, granules, plasters, injections,
capsules), (ii) herbal decoctions (e.g., “tang”), and (iii) plants (whole or extracts). Any type of
drug and placebo comparison and any follow-up duration were considered for inclusion. We
excluded retrieved studies that were published before the year 2000, because the most currently
utilized guidelines for reporting clinical trials (i.e., CONSORT statement) were published in
1996, and we conservatively considered four years to be enough time for these guidelines to be
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disseminated and implemented.[18] We also excluded studies published only as abstracts, studies
with a non-RA control group, and subanalyses of parent studies.
Data collection and outcome measures
One author (X.P.) extracted the data, which were then cross-checked by another author (M.L.-
O.). A standardized extraction form was used to collect information about the characteristics of
the RCTs and their participants, types of interventions, reported outcomes, and sources of
funding. Our primary outcome measures were the methodological and reporting quality of the
RCTs.
Methodological quality in individual studies
The quality of each selected RCT was evaluated independently by two reviewers using the
Cochrane risk of bias tool [20] for RCTs published in English. RCTs published in non-English
languages were translated and evaluated by one reviewer (X.P.) and cross-checked by another
(M.L.-O.). In brief, each RCT was evaluated for its potential bias in five domains: selection,
performance, detection, attrition, and reporting. These domains specifically evaluate how the
random sequence was generated, methods of allocation concealment, blinding of participants and
personnel, blinding of the outcome assessment, how incomplete outcome data was handled, and
if there was evidence of selective outcome reporting. Each potential source of bias was graded as
low, unclear, or high, and a justification for each judgment was provided.
Quality of reporting
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We examined how closely the RCTs adhered to reporting standards using the CONSORT
statement for TCM,[21] which focuses only on CHM (i.e., acupuncture, moxibustion, cupping,
and massage are not considered). It is a 23-item checklist, and the major recommendations for
transparent reporting are i) title and abstract should reflect the unique aspects of TCM, ii)
rationale of formulation selection should be described, iii) diagnostic criteria should be specified
for both TCM and conventional medicine, iv) detailed information on the treatment and control
interventions should be included, v) the outcome in TCM terms should be included, and vi) the
ethics approval number and trial registration number should be included.
Summary measures and synthesis of results
Descriptive statistics were used to report RCT and participant characteristics, as well as the
methodological quality of the RCTs. Risk of bias assessment was summarized per domain.
Bivariate analysis was used to compare RCT characteristics according to the risk of bias
judgment. Univariate and multivariable logistic regressions were performed to determine the
factors associated with high or unclear risk of bias in the five domains in RCTs. We combined
the unclear and high risk of bias categories for the analyses. Evidence suggests that the
magnitude of treatment effects may be similar in studies appraised as having high or unclear risk
of bias, but not for studies assessed as low risk of bias.[22] The variables tested as predictors
were year of publication, sample size, number of authors, publication language (English or non-
English), reporting or disclosing of funding (yes or no), and setting (academic or non-academic).
Variables with a univariate p value <0.15 were initially included in a multivariable logistic
regression model and reduced using the stepwise selection method. Associations were described
using odds ratios (ORs) and their associated 95% confidence intervals (CIs). We categorized
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each CONSORT TCM checklist item as reported or not reported.[21, 23] We then summarized
our findings in five sections: title/abstract, introduction, methods, results, and discussion.
Subgroup analyses were performed to compare rates of potential bias (low risk or unclear/high
risk, unclear versus high risk) and adherence to reporting guidelines according to (i) publication
before or after the Cochrane risk of bias tool was released and (ii) publication before or after the
CONSORT statement for TCM was released. SAS version 9.3 (SAS Institute, Inc., Cary, NC)
was used to carry out the computations for all analyses. Apart from the univariate analysis, p <
0.05 was considered statistically significant.
RESULTS
RCT selection
Out of 2,342 unique citations, 232 full-text articles were retrieved to assess for eligibility. Of
those, 119 RCTs were included [24-142] evaluating 18,919 patients. Figure 1 shows the number
of studies screened, assessed for eligibility, and included in the review, with reasons for
exclusion at each stage.
Characteristics of the included studies
Table 1 shows the aggregated characteristics of the included RCTs, and Supplementary Table 1
shows the characteristics of the individual studies. Two-thirds of the RCTs were published
before the CONSORT statement for TCM and herbal interventions was published (2000-2007).
One RCT was conducted in the United States, one in Korea, and the rest in China. Most were
single-center studies and were not indexed in the ISI Web of Knowledge database but were
indexed in the China National Knowledge Infrastructure database (CNKI).
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Outcomes reported varied across RCTs. More than half of the RCTs assessed efficacy
(e.g., disease activity score either 28 [143] or 44; [144] 20%, 30%, 50%, or 70% improvement,
according to American College of Rheumatology criteria,[145] in tender or swollen joint counts,
physician global assessment, or grip strength; or good to moderate improvement according to
European League Against Rheumatism criteria),[146] laboratory outcomes (e.g., erythrocyte
sedimentation rate, C-reactive protein, rheumatoid factor, or anti-cyclic citrullinated peptides), or
adverse events. However, less than 56% of RCTs reported on patient-reported outcomes (e.g.,
pain, patient global assessment, health assessment questionnaire, or morning stiffness), and only
3% reported radiographic outcomes (e.g., Sharp score, erosion, joint narrowing, marked
radiographic progression, or no progression). Thirty-one RCTs (26%) reported improvement of
symptoms but did not provide additional details on the type of symptoms or how these symptoms
were assessed.
Table 1. Summary of characteristics of the randomized controlled trials (RCTs) included in our
analysis (n = 119).
RCT characteristic No. of RCTs (%)a
Duration
Less than 6 months 93 (78)
More than 6 months 23 (19)
Not reported 3 (3)
Year
2000-2007 (before CONSORT TCM)[19, 23, 147] 80 (67)
2008-2014 39 (33)
Language
English 18 (15)
Chinese 101 (85)
Country
China 117 (98)
Korea 1 (1)
United States 1 (1)
Scope
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Single-center 108 (91)
Multicenter 11 (9)
Impact Factor 2013
Web of Science (score range from 0.59 to 2.711) 13 (11)
Web of Science (score range from 7.871 to 16.104) 4 (3)
Indexed in CNKI (score range from 0.031 to 1.068) 101 (85)
Not indexedb 1 (1)
Outcomesc
Disease activity score 15 (13)
ACR 20/30 28 (24)
Tender joint count 72 (61)
Swollen joint count 78 (66)
Health assessment questionnaire 19 (16)
Pain 53 (45)
Morning stiffness 66 (55)
Laboratory outcomes (ESR, CRP, RF, or anti-CCP) 91 (76)
Radiographic outcomes 3 (3)
Discontinuations 51 (43)
Adverse eventsd 76 (64)
Funding 27 (23)
CHM preparation (main intervention)
Plant or extract (one herb) 3 (3)
Decoction alone 15 (13)
Decoction + patented 2 (2)
Individualized (not following guidelines or with
modifications)
52 (44)
Patented 43 (36)
Patented + individualized 4 (3)
Most common CHM (>1 study)
Tripterygium wilfordii/Tripterygium polyglycosides (alone
or combined)
15 (13)
JuanBi decoction/mixture or Yishen JuanBi capsule
(including those with changes or combined)
11 (9)
Feng Shi decoction/granules/wine/injection (including
those with changes or combined)
10 (8)
Total glucosides of peony 6 (5)
Xinfeng capsule 4 (3)
Zhengqing Fengtongning (alone or combined) 4 (3)
Bi Qi capsule 3 (3)
Lugua polypeptide injection 3 (3)
Guizhi Shaoyao Zhimu decoction 3 (3)
Tongbi (tablets or decoction) 3 (3)
Xiatianwu 3 (3)
Bizhongxiao 2 (2)
Sanbi decoction 2 (2)
Shi Re Bi granule/mixture 2 (2)
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Siwu wuteng decoction 2 (2)
Unspecified (including decoctions without a name) 11 (9) aPercentages have been rounded.
bNot indexed in Web of Science or CNKI.
cRCTs can report on one or more outcomes.
dIncluding either clinical safety or laboratory parameters (alanine transaminase, aspartate
transaminase, creatinine, white blood cell count, platelet count, or hemoglobin).
Abbreviations: ACR 20/30 = American College of Rheumatology criteria for improvement at
20% or 30%; anti-CCP = anti-cyclic citrullinated peptide antibodies; CHM = Chinese herbal
medicine; CNKI = China National Knowledge Infrastructure database; CONSORT TCM =
Consolidated Standards of Reporting Trials statement for traditional Chinese medicine (including
herbal interventions); CRP = C-reactive protein; ESR = erythrocyte sedimentation rate; RF =
rheumatoid factor.
Characteristics of the participants and interventions
Most participants included in the RCTs met the 1987 American College of Rheumatology
diagnostic criteria for RA.[148] One RCT included only patients meeting the 2010 ACR
classification criteria [149] and in another RCT patients included met either the 1987 or 2010
criteria. In addition, 52.5% of the participants met the criteria for one or more of the traditional
TCM “pathological factors” or syndromes (i.e., feng [wind], shi [damp], tan [phlegm], re [heat],
qi, or yin deficiency). The most common pathological factors reported are listed in Table 2. A
total of 10,108 patients received a single CHM and 6,550 received 1 of 11 treatment
combinations. Of those receiving combination treatment, 5,061 patients received combinations
that included CHMs (with disease-modifying antirheumatic drugs, nonsteroidal anti-
inflammatory drugs, steroids, or antibiotics). More than half of the CHMs were individualized
preparations targeting pain relief and improvement in joint function. In the control groups, 1,402
patients received disease-modifying antirheumatic drugs alone, (i.e., methotrexate, leflunomide,
sulfasalazine, or etanercept), 644 received nonsteroidal anti-inflammatory drugs alone, and 165
received an inert placebo. In 35 studies, patients were described as having active disease, and
two RCTs included patients with refractory disease, one included patients with early RA, three
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included patients at intermediate stages of RA, and one included patients with both RA and
anemia. Discontinuation rates were not reported in 68 RCTs, but in those that reported
discontinuation rates, they ranged from 0% to 55%.
Table 2. Characteristics of the participants in the 119 randomized controlled trials included in
our analysis (n = 18,919, ranging from 30 to 3,789 patients per trial)
Characteristic No. of patients (%)
Weighted mean age ± weighted SD 43.5 ± 12.0 years
Female 13,697 (72.4)
Eligibility criteria
ACR RA alone 8,994 (47.5)
ACR RA + 1 TCM syndromea 3,040 (16.1)
ACR RA + 2 TCM syndromesa 332 (1.8)
ACR RA + ≥3 TCM syndromesa 1,072 (5.7)
ACR RA + unspecified number TCM
syndromesa
300 (1.6)
ACR RA + TCM syndrome (not guideline-
driven)
5,181 (27.4)
Median disease duration (range) 5.4 years (0.04-28 years)
Interventions
CHM alone 10,108 (53.4)
CHM + DMARDs 1,595 (8.4)
CHM + DMARDs + NSAIDs 511 (2.7)
CHM + DMARDs + steroids + NSAIDs 79 (0.4)
CHM + steroids 501 (2.6)
CHM + steroids + NSAIDs 200 (1.1)
CHM + NSAIDs 2,101 (11.1)
CHM + NSAIDs + antibiotic 74 (0.4)
DMARDs alone 1,402 (7.4)
DMARDs + steroids 78 (0.4)
DMARDs + steroids + NSAIDs 363 (1.9)
DMARDs + NSAIDs 992 (5.2)
NSAIDs + antibiotic 56 (0.3)
NSAIDs alone 644 (3.4)
Antibioticb 50 (0.3)
Placebo alone 165 (0.9)
Previous WM treatmentc 8,518 (45.0)
Most common patterns reportedd
Dampness-heat blockage 1,023 (10.3)
Dampness-cold and qi deficiency-blood stasis 557 (5.6)
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Heat-cold complex 512 (5.2)
Dampness-cold blockage 300 (3.0)
Dampness-heat and qi deficiency-blood stasis 269 (2.7)
Qi deficiency and blood stasis 226 (2.3)
Yin deficiency 178 (1.8) aChinese medical syndrome following governmental guidelines.
bPenicillin.
cOnly 49 studies reported data.
dPercentages are based on the 46 studies in which eligibility criteria included diagnosis with at
least 1 TCM syndrome (n = 9,925).
ACR RA = American College of Rheumatology classification criteria for rheumatoid arthritis;
CHM = Chinese herbal medicine; DMARDs = disease-modifying antirheumatic drugs; NSAIDs
= nonsteroidal anti-inflammatory drugs; SD = standard deviation; TCM syndrome = traditional
Chinese medicine syndrome; WM = Western medicine.
Quality assessment
Supplementary Figure 1 summarizes the results across RCTs. A high risk of bias across all
domains was observed across all domains. When evaluating selection bias, we found that 29% of
the RCTs did not report sufficient detail to evaluate methods of random sequence generation or
in 31% allocation concealment (judged unclear). In addition, 21% were judged to have high risk
for selection bias (11% from sequence generation, 30% from allocation concealment). Risk of
performance bias (not blinding participants or personnel) was judged to be high in 85% of the
RCTs, and detection bias (blinding of assessment of primary outcome) was judged to be high in
89% of the RCTs. More than two-thirds of the RCTs did not provide sufficient detail to judge the
risk for attrition bias and lacked data on withdrawal rates, power calculation, and how missing
data was handled. From the remaining RCTs providing details to evaluate attrition bias, 4% were
judged to be of high risk. Risk of reporting bias was high in 40% of the RCTs, and 86% of the
RCTs did not report the source of funding or include a disclosure statement.
RCT determinants associated with high risk of bias
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Characteristics observed in RCTs according to risk of bias are shown in Supplementary Table 2.
In the univariate analysis, earlier year of publication, fewer authors, funding source not reported
or disclosed, publication in a language other than English, authors from non-academic settings,
and no power calculation reported were associated with high or unclear risk of bias in various
domains (Table 3). After adjustment for covariates, the following associations remained in the
multivariable analysis: i) earlier year of publication and funding source not reported or disclosed
were associated with high or unclear risk of selection bias (sequence generation); ii) fewer
authors was associated with high or unclear risk of selection bias (allocation concealment),
performance bias, and attrition bias; and iii) publication in a language other than English and
funding source not reported or disclosed was associated with high or unclear risk of reporting
bias. Logistic regression analysis could not be performed for detection bias owing to the small
number of RCTs in the low risk of bias group (n = 2).
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Table 3. Characteristics of randomized controlled trials (RCTs) included in our study (n = 119) associated with high or unclear risk of
bias
Year of
publication
Sample
size
Number of
authors
Language
Funding source
disclosed Affiliationa
Power calculation
includedb
English Chinese Yes No University
Federal/
State Yes No
Selection bias (sequence generation)
Univariate
OR (95% CI) 0.79
(0.70, 0.88)
0.99
(0.99, 1.0)
0.85
(0.75, 0.96) REF
2.6
(0.94, 7.2) REF
7.7
(3.0, 19.8) REF
1.6
(0.74, 3.6) REF
2.2
(0.13, 36.7)
0.0001 0.3 0.01
0.07
<0.0001
0.2
0.6
Multivariable
OR (95% CI) 0.83
(0.73, 0.94) REF
5.0
(1.8, 13.8)
p 0.003
0.002
Selection bias (allocation concealment)
Univariate
OR (95% CI) 0.90
(0.77, 1.1)
0.99
(0.99, 1.0)
0.85
(0.75, 0.96) REF
7.4
(1.9, 29.0) REF
4.0
(1.1, 14.9) REF
1.1
(0.29, 4.2) REF
11.4
(0.66, 197.6)
p 0.2 0.1 0.01
0.004
0.04
0.9
0.09
Multivariable
OR (95% CI)
0.85
(0.75, 0.96)
p
0.01
Performance bias
Univariate
OR (95% CI) 0.87
(0.75, 1.0)
0.99
(0.99, 1.0)
0.83
(0.73, 0.95) REF
7.9
(2.1, 28.5) REF
4.1
(1.2, 14.0) REF
1.2
(0.36, 4.0) REF
51.2
(1.2, 2224.3)
p 0.08 0.2 0.007
0.002
0.02
0.8
0.04
Multivariable
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OR (95% CI)
0.83
(0.73, 0.95)
p
0.007
Attrition bias
Univariate
OR (95% CI) 0.83
(0.74, 0.93)
1.0
(0.99, 1.0)
0.68
(0.56, 0.82) REF
2.7
(0.96, 7.7) REF
3.1
(1.2, 7.6) REF
1.5
(0.66, 3.5) REF
15.0
(0.36, 633.8)
p 0.002 0.7 0.0001
0.06
0.02
0.3
0.2
Multivariable
OR (95% CI)
0.68
(0.56, 0.82)
p
0.0001
Reporting bias
Univariate
OR (95% CI) 0.91
(0.83, 1.0)
0.99
(0.99, 1.0)
0.86
(0.76, 0.98) REF
4.9
(1.5, 16.0) REF
3.5 (1.4,
8.9) REF
2.7
(1.3, 5.8) REF
5.8
(0.14, 243.8)
p 0.06 0.3 0.03
0.008
0.008
0.01
0.4
Multivariable
OR (95% CI)
REF
4.1
(1.2, 13.6) REF
3.0
(1.1, 7.7)
p
0.02
0.03 a
Two RCTs written by authors affiliated with the State and a University were considered part of the University for this analysis. bLogistic regression analysis for detection bias was not performed owing to the small number of RCTs that included power calculation
(n = 2).
Abbreviations: OR = odds ratio; CI = confidence interval.
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Adherence to CONSORT standards for TCM
Rates of adherence to CONSORT standards for TCM are shown in Table 4. Most of the RCTs
(98%) stated the objective adequately. However, most RCTs (94%) did not include the
recommended information (specification of interventions, name of disease, and study design) in
the title or abstract. In the introduction sections, more than half (61%) did not provide the three
names of the compound formulation (Chinese, Latin, and English) as recommended by the
World Health Organization. The methods sections of most RCTs were poorly reported (Table 4).
Most RCTs (ranging from 85% to 98%) failed to describe in enough detail the interventions, type
of study design, calculation of sample size, or methods of randomization and blinding. In the
results sections, many RCTs (78%) did not indicate how participants moved through the study
over time or provide a flow diagram as recommended, and 93% of RCTs did not include
intention-to-treat analysis. The discussion sections were compromised in 8 to 83% of the RCTs
owing to a lack of general interpretation of the results and conflict of interest information.
Table 4. Percentage of randomized controlled trials in our analysis (n = 119) not adherent to
reporting standards provided in the Consolidated Standards of Reporting Trials (CONSORT)
statement for traditional Chinese medicine.
CONSORT item
CONSORT
item no. No. (%)
Title and abstract 1 112 (94)
Introduction
Background 2 73 (61)
Objectives 3 2 (2)
Methods
Participants 4 45 (38)
Interventions 5 101 (85)
Outcomes 6 15 (13)
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Type of study design 7 117 (98)
Sample size 8 117 (98)
Randomization
Sequence generation 9 72 (61)
Allocation concealment 10 109 (92)
Implementation 11 111 (93)
Blinding (masking) 12 107 (90)
Statistical methods 13 48 (40)
Results
Participant flow 14 93 (78)
Recruitment 15 33 (28)
Baseline data 16 31 (26)
Numbers analyzed 17 111 (93)
Outcomes and estimation 18 11 (9)
Ancillary analyses 19 23 (19)
Adverse events 20 40 (34)
Discussion
Interpretation 21 9 (8)
Generalizability 22 14 (12)
Overall evidence 23 99 (83)
Additional analyses
When comparing the risk of bias from the 90 RCTs published before the Cochrane risk of bias
tool was released in 2008 (year of publication 2000-2008) with that of the 29 RCTs published
later, we observed improvement in RCTs published after 2008 in the following domains:
selection bias (22% compared with 59%, p = 0.0004), attrition bias (18% compared with 52%, p
= 0.0005), and reporting bias (41% compared with 66%, p = 0.02). When comparing adherence
to reporting guidelines from the 80 RCTs published before the CONSORT-TCM statement was
released in 2007 (publication date 2000-2007) with that of the 39 RCTs published later, we
observed improvement in RCTs published after 2007 in most of the items except in reporting
sufficient details about the objectives of the study, design, power calculation, and methods to
avoid bias (data not shown). We also evaluated determinants associated with high risk of bias,
compared with unclear risk of bias. In most domains there were no differences. We observed
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differences in allocation concealment, but the characteristics associated with high risk of bias
were the same as those observed with the main comparison high/unclear versus low risk of bias.
There were some characteristics not observed in the main comparison associated with detection
bias (Supplementary Table 3).
DISCUSSION
Our results indicate that serious methodology and reporting flaws still exist in clinical trials
evaluating the effect of CHM in RA. We found that the potential for selection bias was high;
two-thirds of the RCTs in our analysis lacked sufficient detail on how the random sequence was
generated. Similarly, most RCTs were not blinded (e.g., for participants, personnel, or outcome
assessment), thus increasing the potential for both performance and detection bias. Risk of
attrition bias was high or unclear in more than two-third of the RCTs. Reporting bias was also
judged to be high or unclear in half of the included RCTs owing to a lack of study protocol
and/or reporting less than the minimum number of outcome measures recommended to be
included in RA clinical trials.[150] Furthermore, we found that RCTs that were older, had fewer
authors, did not report or disclose funding, were published in a language other than English, or
were written by authors from non-academic settings, were likely to have a high or unclear risk of
bias methodology in at least one of the evaluated domains.
We also found that adherence to reporting standards remains a concern. Title and
abstract, introduction, and methods were even more problematic. Because of these weaknesses,
readers are not provided with clear and transparent information on the interventions or methods
to assess bias in selecting, masking, and evaluating participants. Other areas of concern were
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lack of appropriate general interpretation of the results in the context of current evidence and
incomplete descriptions of conflicts of interest.
It is important to differentiate between the two main concepts reported in this review:
methodological quality and quality of reporting. One of the main components of evidence-based
medicine is the use of available literature to improve decision-making. Stronger inferences can
be drawn from studies in which measures have been taken before, during, and after the
intervention to prevent random and systematic bias. Although RCTs are ranked high in the
hierarchy of evidence, not all RCTs share the same quality, which can lead to biased results.
Quality of reporting is a separate concern. A lack of complete and transparent reporting of the
processes and findings of an RCT is commonly linked to methodological flaws. Poor reporting
leaves out critical information needed to judge study safeguards against bias.
A few systematic reviews evaluating the efficacy of CHM and reporting on the
methodological quality of the studies have shown similar results. However, none of these studies
evaluated CHMs exclusively (i.e., excluding other TCM) in patients with RA. Nonetheless, a
review evaluating the characteristics of 89 studies published between 2000 and 2003 and indexed
in the CNKI reported a lack of unified diagnostic and evaluating standards.[151] Another review
evaluating 20 RCTs published between 2000 and 2010 showed that methodological quality
according to the Jadad scale was generally low, with an average quality score of 1.2 out of
5.[152] Contrastingly, a Cochrane review evaluating herbal medicines in general (including 3
CHMs) showed that the quality of the studies has improved since 2000, but the risk of bias
across different domains was variable.[153] Furthermore, an overview of 31 reviews published
between 1999 and 2009 evaluating several TCM approaches (including CHMs) for multiple
diseases showed that methodological quality improved over the years, although many issues
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remained, specifically a high risk of selection (inadequate randomization methods), attrition
(small sample sizes and high withdrawal rates), and reporting (selective reporting of outcomes)
biases.[154]
To the best of our knowledge, the current study is the first appraising both
methodological quality and adherence to reporting standards specifically in RCTs evaluating
CHM in patients with RA. No other studies have analyzed the characteristics associated with a
high risk of bias or poor adherence to reporting standards. For methodological quality, we used
the risk of bias tool, an instrument endorsed by the Cochrane Collaboration to facilitate improved
appraisal of evidence. The tool has shown significant correlations with other appraisal tools.[155,
156] For example, the risk of bias tool was shown to accurately identify trials that may have
overestimated treatment effects. Studies shown to have a high or unclear risk of bias according to
the risk of bias tool have larger effect estimates than studies shown to have a low risk of bias.[22]
Our study has certain limitations. First, as with any systematic review, it was constrained
by the available data. For example, a protocol or trial registration was not found for most of the
RCTs included in our review. This is concerning because the validity of the conclusion of an
RCT is largely based on adherence to prespecified methods (including outcomes of interest).
Trial registration could improve transparency and help identify gaps in knowledge, prevent
unnecessary duplication in clinical trials, and improve adherence to international quality
standards.[157] Second, we included studies with substantial variation in characteristics (e.g.,
RA diagnosis, TCM syndromes, and CHM descriptions). However, this allowed us to evaluate a
larger number of RCTs. Third, we did not search the CNKI, Chinese Medical Current Contents
(CMCC), and Wanfang Data databases, which could have increased the number of publications
included in this review, because they are not widely available outside Asia, and we felt that there
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was no clear reason to consider that the quality of these studies would have been better.[158]
Lastly, independent quality assessment for non-English language articles could not be performed.
Only one reviewer could translate Chinese articles; therefore, more than 85% of the studies were
evaluated by the translator and cross-checked by another reviewer using the translation from the
first reviewer.
In summary, our results indicate that trials of CHM for the treatment of RA often fail to
meet expected methodological criteria, and high-quality evidence is lacking. Because clinical
trials are just below systematic reviews in the hierarchy of evidence and are used to endorse
recommendations by health organizations, more attention is needed to improve the
methodological robustness of these studies. Future clinical trials evaluating CHMs in RA should
be designed, conducted, and reported according to current specifications and principles.
ACKNOWLEDGMENTS
We are grateful to Yimin Geng from the Research Medical Library of The University of Texas
MD Anderson Cancer Center for helping with the terms included in the search strategies for the
electronic databases and to Ms. Pratibha Nayak for her contributions during the selection of the
studies.
AUTHOR CONTRIBUTIONS
Dr Suarez-Almazor had full access to all of the data in the study and takes responsibility for the
integrity and the accuracy of the data analysis.
Study concept and design: Suarez-Almazor, Lopez-Olivo
Search strategy: Pratt, Geng
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Selection of the studies: Pan, Nayak, Lopez-Olivo
Quality appraisal and data extraction: Pan, Lopez-Olivo
Analysis and interpretation of data: Song, Pan, Lopez-Olivo, Suarez-Almazor
Drafting of the manuscript: Pan, Lopez-Olivo, Song, Suarez-Almazor
Critical revision of the manuscript for important intellectual content: Pan, Lopez-Olivo,
Song, Pratt, Suarez-Almazor
Administrative, technical, or material support: Suarez-Almazor
Study supervision: Suarez-Almazor
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FIGURE LEGENDS
Figure 1. Flow chart of included studies. Abbreviations: RA = rheumatoid arthritis; CHM =
Chinese herbal medicine.
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145. Felson DT, Anderson JJ, Boers M, et al. American College of Rheumatology. Preliminary
definition of improvement in rheumatoid arthritis. Arthritis Rheum 1995;38(6):727-35
146. van Gestel AM, Prevoo ML, van 't Hof MA, van Rijswijk MH, van de Putte LB, van Riel
PL. Development and validation of the European League Against Rheumatism response
criteria for rheumatoid arthritis. Comparison with the preliminary American College of
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Criteria. Arthritis Rheum 1996;39(1):34-40
147. 吴泰相, 李幼平, 卞兆祥, et al. 中医药临床随机对照试验报告规范(征求意见稿). 中国循
证医学杂志 2007(08):601-05
148. Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987
revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum 1988;31(3):315-
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149. Aletaha D, Neogi T, Silman AJ, et al. 2010 rheumatoid arthritis classification criteria: an
American College of Rheumatology/European League Against Rheumatism collaborative
initiative. Annals of the rheumatic diseases 2010;69(9):1580-8 doi:
10.1136/ard.2010.138461published Online First: Epub Date]|.
150. Bykerk VP, Lie E, Bartlett SJ, et al. Establishing a core domain set to measure rheumatoid
arthritis flares: report of the OMERACT 11 RA flare Workshop. J Rheumatol
2014;41(4):799-809 doi: 10.3899/jrheum.131252published Online First: Epub Date]|.
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151. Kim YW, Zhang MQ. Characteristics of traditional Chinese medicine in treating
rheumatoid arthritis: A retrospective analysis. [Chinese]. Chinese Journal of Clinical
Rehabilitation 2005;9(15):152-55
152. Zhang C, Jiang M, Lu A. Chinese herbal medicines versus disease modifying antirheumatic
drugs for management of rheumatoid arthritis: A systematic review. Eur J Integr Med
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Epub Date]|.
153. Cameron M, Gagnier JJ, Chrubasik S. Herbal therapy for treating rheumatoid arthritis.
Cochrane Db Syst Rev 2011(2) doi: Artn Cd002948
Doi 10.1002/14651858.Cd002948.Pub2published Online First: Epub Date]|.
154. Jiang M, Yang J, Zhang C, et al. Clinical studies with traditional Chinese medicine in the
past decade and future research and development. Planta Medica 2010;76(17):2048-64 doi:
http://dx.doi.org/10.1055/s-0030-1250456published Online First: Epub Date]|.
155. Jadad AR, Moore RA, Carroll D, et al. Assessing the quality of reports of randomized
clinical trials: is blinding necessary? Controlled clinical trials 1996;17(1):1-12
156. Schulz KF, Chalmers I, Hayes RJ, Altman DG. Empirical evidence of bias. Dimensions of
methodological quality associated with estimates of treatment effects in controlled trials.
Jama 1995;273(5):408-12
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157. Califf RM, Zarin DA, Kramer JM, Sherman RE, Aberle LH, Tasneem A. Characteristics of
clinical trials registered in ClinicalTrials.gov, 2007-2010. Jama 2012;307(17):1838-47 doi:
10.1001/jama.2012.3424published Online First: Epub Date]|.
158. Wu XY, Tang JL, Mao C, Yuan JQ, Qin Y, Chung VC. Systematic reviews and meta-
analyses of traditional chinese medicine must search chinese databases to reduce language
bias. Evid Based Complement Alternat Med 2013;2013:812179 doi:
10.1155/2013/812179published Online First: Epub Date]|.
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Figure 1. Flow chart of included studies. Figure 1
203x213mm (300 x 300 DPI)
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Appendix 1. Medline search strategy
Database(s): Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations and Ovid
MEDLINE(R), 1946 to June 2015
No. Search terms
1 RHEUMATOID ARTHRITIS/
2 ((rheumatoid or reumatoid) adj3 (arthriti* or artriti*)).mp.
3 ra.ti.
4 (rheumatism* or rheumarthriti * or antirheumatic* or anti-rheumatic*).ti,ab.
5 ((rheumatic or reumatic) adj3 (arthriti* or polyarthriti*)).ti,ab.
6 rheumat*.jw.
7 or/1-6
8 exp MEDICINE, CHINESE TRADITIONAL/
9 DRUGS, CHINESE HERBAL/
10 TCM.ti.
11 ((China* or Chinese*) adj3 (medicin* or traditional* or natural* or patent*)).mp.
12 ((China* or Chinese*) adj5 herb* adj5 (drug* or prepar* or formula* or pharmac* or
prescri* or mixture* or drink*)).mp.
13 ((China* or Chinese*) adj5 (decoct* or extract* or remedy or remedies or soup* or
infusion*)).mp.
14 ((China* or Chinese*) adj5 (ethnopharm* or phytotherap* or phytomedicin* or
ethnobotanical*)).mp.
15 "Chinese materia medica*".mp.
16 ("zhong yao" or "zhong yi" or "zhongyao" or "zhongyi").mp.
17 or/8-16
18 7 and 17
19 PLANTS, MEDICINAL/
20 ETHNOPHARMACOLOGY/
21 exp PHYTOTHERAPY/
22 exp PLANT PREPARATIONS/
23 exp PLANT ROOTS/
24 plant extracts.rn.
25 or/19-24
26 (China* or Chinese* or "Hong Kong*" or Sino* or Taiwan*).mp.
27 chinese.lg.
28 (China* or Chinese* or "Hong Kong*" or Sino* or Taiwan*).in.
29 (China* or Chinese* or "Hong Kong*" or Taiwan*).jw.
30 (China* or Chinese* or "Hong Kong*" or Taiwan*).cp.
31 or/26-30
32 25 and 31
33 7 and 32
34 TRIPTERYGIUM/
35 ("Tripterygi* wilfordi*" or "thunder god vine*" or "Lei Gong Teng" or LeiGongTeng or
triptolide or celastrol).mp.
36 exp PAEONIA/
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37 (peony* or paeonia* or "Bai Shao" or BaiShao).mp.
38 SAUSSUREA/
39 (Xuelian or Xue Lian or Saussurea).mp.
40 SINOMENIUM/
41 (Zheng Qing Feng Tong Ning or ZhengQing FengTongNing or Sinomeni*).mp.
42 or/34-41
43 7 and 42
44 Tripterygi* Hypoglauc*.mp.
45 Aconit* Kusnezofi*.mp.
46 Aconit* Carmichael*.mp.
47 Cyathul*.mp.
48 Clematid*.mp.
49 Rehmanni*.mp.
50 Spatholob*.mp.
51 Seolopendr*.mp.
52 Scorpio*.mp.
53 Stephani*.mp.
54 Ephedr*.mp.
55 Glycyrrhiz*.mp.
56 Angelic* Sinensi*.mp.
57 Gentian* Macrophyll*.mp.
58 Astragal*.mp.
59 Asari*.mp.
60 Notopterygi*.mp.
61 (Chuanxiong* or Chuan xiong*).mp.
62 Saposhnikovi*.mp.
63 Angelic* Pubescent*.mp.
64 Lateral* Praeparat*.mp.
65 Cinnamom*.mp.
66 Anemarrhen*.mp.
67 Paeoni* Alba*.mp.
68 Terminali*.mp.
69 Cartham*.mp.
70 or/44-69
71 7 and 70
72 (San Zi Yang Qin* or SanZiYangQin*).mp.
73 (Huo Luo Xiao Ling* or HuoLuoXiaoLing*).mp.
74 (Yi Wei* or YiWei*).mp.
75 (Sheng Yang Yi Wei* or ShengYangYiWei*).mp.
76 (San Miao Wan* or SanMiaoWan*).mp.
77 (Si Ni* or SiNi).mp.
78 (Dang Gui Si Ni* or DangGuiSiNi*).mp.
79 (Wu Tou* or WuTou*).mp.
80 (Shen Tong Zhu Yu* or ShenTongZhuYu*).mp.
81 (Huang Qi Gui Zhi Wu Wu* or Huang QiGuiZhiWuWu*).mp.
82 (Bai Hu Jia Gui Zhi* or BaiHuJiaGuiZhi*).mp.
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83 (Xuan Bi* or XuanBi*).mp.
84 (Du Huo Ji Sheng* or DuHuoJiSheng*).mp.
85 (Si Wu* or SiWu*).mp.
86 (Tao Hong si Wu* or TaoHongSiWu*).mp.
87 (Gui Zhi* or GuiZhi*).mp.
88 (Juan Bi* or JuanBi*).mp.
89 (Xiao Huo Luo* or XiaoHuoLuo*).mp.
90 (Ma Huang Fu Zi Gan Cao* or MaHuangFuZiGanCao*).mp.
91 (Fu Zi* or FuZi).mp.
92 (Fang Feng* or FangFeng*).mp.
93 (Yi Yi Ren* or YiYiRen*).mp.
94 (Si Jun Zi* or SiJunZi*).mp.
95 (Xiao Jian Zhong* or XiaoJianZhong*).mp.
96 (Huang Qi Jian Zhong* or HuangQiJianZhong*).mp.
97 (San Bi* or SanBi).mp.
98 (Yang He* or YangHe*).mp.
99 (Ren Shen Yang Rong* or RenShenYangRong*).mp.
100 (Bai Hu* or BaiHu).mp.
101 (Qing Ying* or QingYing*).mp.
102 (Tong Xie Yao Fang* or TongXieYaoFang*).mp.
103 (Xue Fu Zhu Yu* or XueFuZhuYu*).mp.
104 or/72-103
105 7 and 104
106 (Chuan Xiong Qin* or ChuanXiongQin*).mp.
107 (Huang Qi* or HuangQi*).mp.
108 (Shi Re Bi* or ShiReBi*).mp.
109 (Zhuang Gu* or ZhuangGu*).mp.
110 (Pan Long Qi* or PanLongQi*).mp.
111 (Kun Ming Shan Hai Tang* or KunMingShanHaiTang*).mp.
112 (Zheng Qing Feng Tong Ning* or ZhengQingFengTongNing*).mp.
113 (Yu Xue Bi* or YuXueBi*).mp.
114 (Han Shi Bi* or HanShiBi*).mp.
115 (Lei Gong Teng* or LeiGongTeng*).mp.
116 (Lei Gong Teng Duo Dai* or LeiGongTengDuoDai*).mp.
117 (Huo Luo* or HuoLuo*).mp.
118 (Bao An Wan Ling* or BaoAnWanLing*).mp.
119 (Shou Feng Shun Qi* or ShouFengShunQi*).mp.
120 (Feng Shi* or FengShi*).mp.
121 (Gu Ci Xiao Tong* or GuCiXiaoTong*).mp.
122 (Fu Fang Xia Tian Wu* or FuFangXiaTianWu*).mp.
123 (Xia Tian Wu* or XiaTianWu*).mp.
124 (Er Xian* or ErXian*).mp.
125 (Zhui Feng Tou Gu* or ZhuiFengTouGu*).mp.
126 (Hong Hua* or HongHua*).mp.
127 (She Xiang Zhui Feng* or SheXiangZhuiFeng*).mp.
128 (Zhui Feng* or ZhuiFeng*).mp.
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129 (Shen Jin Huo Luo* or ShenJinHuoLuo*).mp.
130 (Xiao Huo Luo* or XiaoHuoLuo*).mp.
131 or/106-130
132 7 and 131
133 (zushima* or zu shi ma*).mp.
134 (biqi* or bi qi*).mp.
135 (wangbi* or wang bi*).mp.
136 Yishen Juanbi*.mp.
137 Yi shen Juan bi*.mp.
138 Shiguogong*.mp.
139 Shi guo gong*.mp.
140 Yunnan Baiyao*.mp.
141 Yun nan Bai yao*.mp.
142 Daphne*.mp.
143 Feng Shi*.mp.
144 FengShi*.mp.
145 or/133-144
146 7 and 145
147 18 or 33 or 43 or 71 or 105 or 132 or 146
148 (animals not (humans and animals)).sh.
149 147 not 148
150 (case reports not (case reports and review)).pt.
151 case report*.ti. not review.pt.
152 150 or 151
153 149 not 152
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Supplementary Figure 1. Risk of bias across randomized controlled trials included in our
analysis (n = 119), evaluated using the Cochrane risk of bias assessment tool.[20]
0% 20% 40% 60% 80% 100%
Other bias
Reporting bias
Attrition bias
Detection bias
Performance bias
Selection bias (allocation concealment)
Selection bias (sequence generation)
Low Unclear High
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Supplementary Table 1. Characteristics of each included study.
Study, year [ref] Year Language Country Centers Intervention
arms
Sample
size
Eligibility criteria Affiliation
Chen 2013 [24] 2013 EN China 1 3 1784 ACR RA University
Chen 2013 [25] 2013 EN China 3 2 194 ACR RA University
Chen 2010 [26] 2010 CHN China 1 2 90 ACR RA State
Du 2005 [27] 2005 CHN China 1 2 61 ACR RA State
Fan 2007 [28] 2007 CHN China 1 2 96 ACR RA+TCM guideline (≥3) State
Goldbach-Mansky
2009 [29] 2009 EN US
11 2 121 ACR RA Federal
He 2008 [30] 2014 CHN China 1 2 46 ACR RA University
Ji 2002 [31] 2002 EN China 1 2 82 ACR RA State
Jiang 2012 [32] 2012 EN China 1 2 86 ACR RA University
Jiao 2012 [33] 2012 CHN China 1 2 67 ACR RA+TCM guideline (1) Federal
Jie 2012 [34] 2012 CHN China 2 3 138 ACR RA+TCM guideline (1) University
Kang 2010 [35] 2010 CHN China 1 2 38 ACR RA+TCM guideline (1) University
Li 2007 [36] 2007 EN China-Hong
Kong 1 2 65
ACR RA University
Li 2002 [37] 2002 CHN China 1 2 30 ACR RA University
Li 2006 [38] 2006 CHN China 1 2 120 ACR RA State
Liang 2000 [39] 2000 CHN China 1 2 96 ACR RA+TCM guideline (1) State
Lin 2011 [40] 2011 CHN China 5 3 240 ACR RA University
Liu 2008 [41] 2008 CHN China 1 2 90 ACR RA+TCM guideline (1) State
Liu 2006 [42] 2006 CHN China 1 3 40 ACR RA University
Liu 2006 [43] 2006 CHN China 1 2 120 ACR RA University
Liu 2007 [44] 2007 CHN China 1 2 120 ACR RA+TCM guideline (1) University
Liu 2006 [45] 2006 CHN China 1 2 142 ACR RA+TCM guideline (2) University
Liu 2009 [46] 2009 CHN China 1 2 100 ACR RA+TCM guideline (1) State
Lu 2002 [47] 2002 CHN China 1 2 60 ACR RA State
Shen 2011 [48] 2011 EN China 1 2 80 ACR RA+TCM guideline (1) University
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Shen 2003 [49] 2003 EN China 1 2 106 ACR RA State(City)
Song 2007 [50] 2007 EN Korea 7 2 183 ACR RA University
Tao 2002 [51] 2002 EN China 1 3 35 ACR RA Federal
Wang 2013 [52] 2013 CHN China 1 2 240 ACR RA+TCM guideline (1) Federal
Wu 2001 [53] 2001 CHN China 1 2 70 ACR RA State
Yang 2003 [54] 2003 EN China 1 2 60 ACR RA+TCM guideline (1) State
Yu 2007 [55] 2007 CHN China 1 3 70 ACR RA+TCM guideline (≥3) State
Yu 2013 [56] 2013 CHN China 1 3 230 ACR RA+TCM guideline (1) State(City)
Yu 2005 [57] 2005 EN China 1 2 90 ACR RA University
Zhang 2007 [58] 2007 CHN China 1 2 84 ACR RA State
Zhao 2012 [59] 2012 CHN China 1 2 104 ACR RA University
Zhao 2006 [60] 2006 CHN China 1 2 80 ACR RA University
Zhou 2009 [61] 2009 CHN China 1 2 78 ACR RA+TCM guideline (1) Federal
Zhou 2010 [62] 2010 CHN China 1 2 120 ACR RA+TCM guideline (1) Federal
Zhou 2002 [63] 2002 CHN China 1 2 170 ACR RA+TCM guideline (1) State(City)
Zhou 2006 [64] 2006 CHN China 1 2 80 ACR RA University
Zhou 2000 [65] 2000 EN China 1 3 128 ACR RA+TCM guideline (2) University
Zhou 2004 [66] 2004 EN China 1 2 118 ACR RA+TCM guideline (1) University
Zhang 2006 [67] 2006 CHN China 1 2 150 ACR RA University
Zuo 2009 [68] 2009 CHN China 1 2 78 ACR RA University
Sun 2002 [69] 2002 EN China 1 2 76 ACR RA State(City)
Li 2013 [70] 2013 CHN China 1 2 118 ACR RA+TCM guideline (1) University
Hang 2005 [71] 2005 CHN China 6 2 240
ACR RA+TCM Sx_no
guidelines
State(City) and
University
Xun 2010 [72] 2010 CHN China 1 2 86 ACR RA+TCM guideline (1) University
Ding 2010 [73] 2010 CHN China 1 2 63 ACR RA State(City)
Tang 2002 [74] 2002 CHN China 1 2 91 ACR RA Federal
Tu 2006 [75] 2006 CHN China 1 2 80 ACR RA University
Guo 2003 [76] 2003 CHN China 1 3 328 ACR RA Federal
Chen 2005 [77] 2005 CHN China 1 2 44 ACR RA State(City)
Guan 2005 [78] 2005 CHN China 1 2 80 ACR RA University
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Ma 2008 [79] 2008 CHN China 1 2 189
ACR RA+TCM Sx_no
guidelines State(City)
Hu 2007 [80] 2007 CHN China 1 2 74 ACR RA State(City)
Li 2003 [81] 2003 CHN China 1 2 60 ACR RA University
Liu 2000 [82] 2000 CHN China 1 2 80 ACR RA State(City)
Wang 2001 [83] 2001 CHN China 1 2 322
ACR RA+TCM Sx_no
guidelines State(City)
Xiao 2008 [84] 2008 CHN China 1 2 96 ACR RA State(City)
Zou 2007 [85] 2007 CHN China 1 2 60
ACR RA+TCM guideline
(unspecified #) State(City)
Wang 2006 [86] 2006 CHN China 1 2 60 ACR RA State(City)
Ma 2002 [87] 2002 CHN China 1 2 360 ACR RA+TCM guideline (≥3) State(City)
Wu 2004 [88] 2004 CHN China 1 2 86
ACR RA+TCM Sx_no
guidelines University
Jiang 2000 [89] 2000 CHN China 1 2 280 ACR RA State(City)
Liang 2000 [90] 2000 CHN China 1 2 66 ACR RA State
Tao 2002 [91] 2002 CHN China 1 2 70 ACR RA State(City)
Lv 2000 [92] 2000 CHN China 1 2 72 ACR RA University
Zhang 2005 [93] 2005 CHN China 1 2 80 ACR RA+TCM guideline (1) State(City)
Chen 2005 [94] 2005 CHN China 1 2 82 ACR RA University
Xiao 2008 [95] 2008 CHN China 1 2 110 ACR RA State(City)
Huang 2007 [96] 2007 CHN China 1 2 196 ACR RA University
Fan 2000 [97] 2000 CHN China 1 2 129 ACR RA State(City)
Zhen 2006 [98] 2006 CHN China 1 2 50 ACR RA+TCM guideline (1) State(City)
Ji 2008 [99] 2008 CHN China 1 2 101 ACR RA State(City)
Xu 2005 [100] 2005 CHN China 1 2 200
ACR RA+TCM Sx_no
guidelines State(City)
Wang 2006 [101] 2006 CHN China 1 3 150 ACR RA State(City)
Liu 2007 [102] 2007 CHN China 1 2 52 ACR RA State(City)
He 2001 [103] 2001 CHN China 1 2 62 ACR RA+TCM guideline (2) State(City)
Liu 2003 [104] 2003 CHN China 1 2 3789
ACR RA+TCM Sx_no
guidelines State(City)
Huang 2002 [105] 2002 CHN China 1 2 59 ACR RA State(City)
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Li 2001 [106] 2001 CHN China 1 2 78 ACR RA State
Li 2003 [107] 2003 CHN China 1 2 160
ACR RA+TCM guideline
(unspecified #) Rural
Xin 2005 [108] 2005 CHN China 1 2 90 ACR RA State(City)
Leng 2000 [109] 2000 CHN China 1 2 80 ACR RA University
Wang 2005 [110] 2005 CHN China 1 2 168 ACR RA State(City)
Zeng 2006 [111] 2006 CHN China 1 2 70 ACR RA State(City)
Ji 2007 [112] 2007 CHN China 1 2 80 ACR RA State(City)
Cai 2006 [113] 2006 CHN China 1 2 90
ACR RA+TCM Sx_no
guidelines State(City)
Wu 2004 [114] 2004 CHN China 1 2 56 ACR RA University
Guo 2003 [115] 2003 CHN China 1 2 200 ACR RA State(City)
Li 2008 [116] 2008 CHN China 1 2 60
ACR RA+TCM Sx_no
guidelines State
Chen 2007 [117] 2007 CHN China 1 2 140 ACR RA State(City)
Li 2003 [118] 2003 CHN China 1 2 57 ACR RA+TCM guideline (≥3) State(City)
Du 2003 [119] 2003 CHN China 1 2 80 ACR RA State(City)
Xu 2004 [120] 2004 CHN China 1 2 63 ACR RA State
Shi 2007 [121] 2007 CHN China 1 2 88 ACR RA State(City)
Hui 2008 [122] 2008 CHN China 1 2 60 ACR RA State
Meng 2006 [123] 2006 CHN China 1 2 60 ACR RA State
Wang 2004 [124] 2004 CHN China 1 2 122
ACR RA+TCM Sx_no
guidelines State(City)
He 2014 [125] 2014 CHN China 1 2 88 ACR RA+TCM guideline (1) State
Huang 2013 [126] 2014 EN China 1 2 300 ACR RA University
Kou 2013 [127] 2014 EN China 9 2 489 ACR RA+TCM guideline (≥3)
State and
University
Liu 2014 [128] 2013 CHN China 4 2 212 ACR RA+TCM guideline (1) Federal
Wang 2014 [129] 2013 CHN China 1 2 80
ACR RA+TCM guideline
(unspecified #) University
Guo 2008 [130] 2008 CHN China 1 2 50 ACR RA University
Tao 2011 [131] 2011 CHN China 1 2 105 ACR RA Federal
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Zhu 2011 [132] 2011 CHN China 1 2 41 ACR RA University
Zheng 2009 [133] 2009 CHN China 2 2 102 ACR RA+TCM guideline (1) University
Liu 2003 [134] 2003 CHN China 1 2 40 ACR RA University
Sun 2003 [135] 2003 CHN China 1 2 60 ACR RA+TCM guideline (1) University
Cui 2004 [136] 2004 CHN China 1 2 108 ACR RA State(City)
Liu 2008 [137] 2008 CHN China 5 2 439 ACR RA+TCM guideline (1) State
Ao 2005 [138] 2005 CHN China 1 2 60 ACR RA+TCM guideline (1) University
Wu 2001 [139] 2001 CHN China 1 2 70 ACR RA State
Wang 2007 [140] 2007 CHN China 1 2 62 ACR RA State(City)
He 2002 [141] 2002 CHN China 1 2 83
ACR RA+TCM Sx_no
guidelines State
Lv 2014 [142] 2014 EN China 9 3 207 ACR RA University
ACR RA=American College of Rheumatology Classification Criteria for rheumatoid arthritis; CHN=Chinese; ENG=English;
TMC=Traditional Chinese Medicine; Sx=Syndrome
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Supplementary Table 2. Characteristics of randomized controlled trials (RCTs) included in our analysis (n = 119) according to risk
of bias.a
Characteri
stic
Selection bias
(random sequence)
Selection bias
(allocation
concealment) Performance bias Detection bias Attrition bias Reporting bias High/
unclear, n
= 82
Low,
n =
37 p
High/
unclear,
n = 109
Low,
n =
10 p
High/
unclear,
n = 107
Low,
n =
12 p
High/
unclear,
n = 117
Low,
n = 2 p
High/
unclear,
n = 88
Low
, n =
31 p
High/
unclear,
n = 63
Low,
n =
56 p
Mean year
of
publication
±SD
2005 ±
3.6
2008.5
± 3.7 <0.0001
2006 ±
3.8
2007.
7 ±
4.6
0.3 2006 ±
3.8
2008 ±
4.2 0.09
2006 ±
3.9
2011
± 4.2 0.09 2005.5
± 3.6
2008 ±
4.2 0.003 2005.6
± 3.6
2007±
4.1 0.1
Mean
sample size
± SD
130.5 ±
197.4
222.1
±
610.8
0.6 111.4 ±
73.2
677
±
1215.
4
0.3 141.8 ±
361.8
312.1 ±
487.3 0.3
156.2 ±
379.7
323 ±
164.1 0.04
166.4 ±
435.2
138.0
±
100.6
0.1 113.7 ±
78.5
209.9
±
541.8
0.9
Mean no.
of authors
± SD
3.7 ±
2.6
6.1 ±
6.0 0.007
4.0 ±
3.6
8.9 ±
6.1 0.002
4.0 ±
3.6
8.8 ±
5.9 0.0008
4.2 ±
3.2
18.5
±
19.1
0.09 3.4 ±
2.0
7.5 ±
6.4 <0.0001
3.6 ±
4.1
5.4 ±
3.9 0.0004
Mean
Impact
Factor ±
SD
0.48 ±
0.45
1.8 ±
3.2 <0.0001
0.62 ±
0.95
4.0 ±
5.2 0.0005
0.60 ±
0.94
3.6 ±
4.8 0.0002
0.83 ±
1.8
4.8 ±
6.4 0.5
0.50 ±
0.45
2.0 ±
3.5 <0.0001
0.55 ±
1.2
1.3 ±
2.5 <0.0001
No. of non-
English
language
(%)
73 (89) 28
(75.7) 0.06
96
(88.1)
5
(50) 0.007
95
(88.8) 6 (50) 0.003
100
(85.5)
1
(50) 0.3
78
(88.6)
23
(74.2) 0.08
59
(93.7)
42
(75) 0.005
No. of
RCTs with
no source
73 (89) 19
(51.4) <0.0001
87
(79.8)
5
(50) 0.05
86
(80.4) 6 (50) 0.03
91
(77.8)
1
(50) 0.4 73 (83)
19
(61.3) 0.01
55
(87.3)
37
(66.1) 0.006
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of funding
listed (%)
No. non-
academic
RCTs (%)
54
(65.9)
20
(54.1) 0.2
68
(62.4)
6
(60) 1
67
(62.6) 7 (58.3) 0.8
73
(62.4)
1
(50) 1
57
(64.8)
17
(54.8) 0.3 46 (73)
28
(50) 0.01
No. of
RCTs with
no power
calculation
provided
(%)
81
(98.8)
36
(97.3) 0.5
108
(99.1)
9
(90) 0.2
107
(100)
10
(83.3) 0.009
115
(98.3)
2
(100) 1
88
(100)
29
(93.5) 0.07
63
(100)
54
(96.4) 0.2
aRCTs judged to have an unclear risk of bias were merged with those judged to have a high risk of bias. bEither Impact Factor (2013) or the China National Knowledge Infrastructure database was used. cTwo RCTs written by authors affiliated with the State and a University were part of the University for this analysis
Abbreviations: SD = standard deviation.
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Supplementary Table 3. Characteristics of randomized controlled trials (RCTs) included in our analysis according to comparison of
high risk vs. unclear
Characteristic
Selection bias
(random sequence)
Selection bias
(allocation
concealment) Performance bias Detection bias Attrition bias Reporting bias
High,
n =13
Unclear,
n = 69 p
High,
n = 36 Unclear,
n=73 P
High,
n = 101 Unclear, n = 6 p
High,
n = 106 Unclear,
n =11 p
High,
n = 5 Unclear,
n = 83 p
High,
n = 48 Unclear,
n=15 p
Mean year of
publication
±SD
2005 ±
3.5
2005.2
± 3.6
0.9 2007.2
± 4.06
2005.
6 ±
3.6
0.05 2006.1
± 3.9
2005.3
± 3.0
0.8 2005.9
± 3.8
2008.2
± 4.4
0.1 2008.4
± 4.5
2005.4 ±
3.5
0.1 2005.1
± 3.6
2007.1
± 3.2 0.05
Mean sample
size ± SD
101.4 ±
36.1
136.0 ±
214.5
0.7 109.7 ±
51.6
112.3
±
82.0
0.2 143.6 ±
372.3
109.2 ±
46.6
0.5 141.2 ±
363.5
300.6 ±
509.4
0.5 115.6 ±
46.9
169.4 ±
448.0
0.3 107.6 ±
71
133.4
± 99.1
0.3
Mean no. of
authors ± SD
4.2 ±
2.3
3.6 ±
2.7
0.3 4.4 ±
1.8
3.9 ±
4.3 0.005 4.0 ±
3.7
3.3 ±
2.0
0.7 3.7 ±
2.3
9.1 ±
6.0
0.00
07
3.4 ±
1.5
3.4 ± 2.0 0.8 3.8 ±
4.6
2.8 ±
1.7
0.4
Mean Impact
Factor ± SD
0.47 ±
0.27
0.48 ±
0.48
0.6 0.83 ±
0.39
0.51
±
1.11
<0.000
1
0.61 ±
0.96
0.45 ±
0.27
0.8 0.51 ±
0.39
3.9 ±
4.9
<0.0
001
1.0 ±
1.0
0.46 ±
0.38
0.2 0.62 ±
1.3
0.33 ±
0.27
0.4
No. of non-
English
language (%)
12
(92.3)
61
(88.4)
1.0 27 (75) 69
(94.5) 0.009 89
(88.1)
6 (100) 1.0 95
(89.6)
5 (45.5) 0.00
1
3 (60) 75 (90.4) 0.1 44
(91.7)
15
(100) 0.6
No. of RCTs
with no source
of funding
listed (%)
12
(92.3)
61
(88.4)
1.0 24
(66.7)
63
(86.3) 0.02 80
(79.2)
6 (100) 0.6 86
(81.1)
5 (45.5) 0.02 5 (100) 68 (81.9) 0.6 41
(85.4)
14
(93.3) 0.4
No. non-
academic RCTs
(%)
8
(61.5)
46
(66.7)
0.8 18 (50) 50
(68.5)
0.06 64
(63.4)
3 (50) 0.7 67
(63.2)
6 (54.5) 0.7 2 (40) 55 (66.3) 0.3 33
(68.8)
13
(86.7) 0.3
No. of RCTs
with no power
calculation
provided (%)
13
(100)
68
(98.6)
1.0 36
(100)
72
(98.6)
1.0 101
(100)
6 (100) - 106
(100)
9 (81.8) 0.00
81
5 (100) 83 (100) - 48
(100)
15
(100)
-
Abbreviations: SD = standard deviation.
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PRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 Checklist
Section/topic # Checklist item Reported on page #
TITLE
Title 1 Identify the report as a systematic review, meta-analysis, or both. 1
ABSTRACT
Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.
4-5
INTRODUCTION
Rationale 3 Describe the rationale for the review in the context of what is already known. 7-8
Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).
8
METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
NA
Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered,
language, publication status) used as criteria for eligibility, giving rationale. 9
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.
8-9
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.
Suppl. File
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
9
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
9-10
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
10
Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
10
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). 11
Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency
(e.g., I2) for each meta-analysis.
11
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PRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 ChecklistPRISMA 2009 Checklist
Page 1 of 2
Section/topic # Checklist item Reported on page #
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
10
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
11
RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
12 & Figure 1
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
12 & Table 1
Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). 16
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
NA
Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. 17 & Table 3
Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Suppl. Fig.
Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). 22
DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).
23
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).
25
Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. 25
FUNDING
Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.
2
From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(6): e1000097. doi:10.1371/journal.pmed1000097
For more information, visit: www.prisma-statement.org. Page 2 of 2
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