bmjopen.bmj.comFor peer review only PRISMA 2009 Checklist Page 1 of 2 Section/topic # Checklist item Reported on page # Risk of bias across studies 15 Specify any assessment of risk

For peer review only

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:

[email protected].

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)


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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139. He D, Shen J, Zhang Z, Lao Z. “Shi Re Bi Granule” for Rheumatoid Arthritis in 46 Cases. .

Shanghai Journal of Traditional Chinese Medicine 2002;36(12):14-5

140. Lv QW, Zhang W, Shi Q, et al. Comparison of Tripterygium wilfordii Hook F with

methotrexate in the treatment of active rheumatoid arthritis (TRIFRA): a randomised,

controlled clinical trial. Annals of the rheumatic diseases 2014 doi: 10.1136/annrheumdis-

2013-204807published Online First: Epub Date]|.

141. Prevoo ML, van 't Hof MA, Kuper HH, van Leeuwen MA, van de Putte LB, van Riel PL.

Modified disease activity scores that include twenty-eight-joint counts. Development and

validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis

Rheum 1995;38(1):44-8

142. van der Heijde DM, van 't Hof M, van Riel PL, van de Putte LB. Development of a disease

activity score based on judgment in clinical practice by rheumatologists. J Rheumatol

1993;20(3):579-81

143. 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

144. 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

Rheumatology and the World Health Organization/International League Against Rheumatism

Criteria. Arthritis Rheum 1996;39(1):34-40

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145. 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

146. 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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147. Aletaha D, Neogi T, Silman AJ, et al. 2010 rheumatoid arthritis classification criteria: an

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148. 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

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149. Kim YW, Zhang MQ. Characteristics of traditional Chinese medicine in treating

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151. Cameron M, Gagnier JJ, Chrubasik S. Herbal therapy for treating rheumatoid arthritis.

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152. 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:

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153. 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

154. 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

155. Hartling L, Ospina M, Liang Y, et al. Risk of bias versus quality assessment of randomised

controlled trials: cross sectional study. BMJ (Clinical research ed.) 2009;339:b4012 doi:

10.1136/bmj.b4012published Online First: Epub Date]|.

156. 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]|.

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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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129 (Shen Jin Huo Luo* or ShenJinHuoLuo*).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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Page 1 of 2


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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Journal: BMJ Open

Manuscript ID bmjopen-2016-013242.R1


Date Submitted by the Author: 01-Dec-2016




Rheumatology




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1




2, Juhee Song

3, Gregory Pratt


2.









[email protected].








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2



Word count: 3,708


Number of tables: 4



SOURCE OF FUNDING




COMPETING INTERESTS









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3







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4

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.


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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5

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.


high-quality evidence is lacking.



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6

STRENGTHS OF THIS STUDY



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



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













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90%.[15]

















METHODS



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Information sources


















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.






RCTs.












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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






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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






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





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were assessed.


analysis (n = 119).


Duration



Not reported 3 (3)

Year


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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Multicenter 11 (9)

Impact Factor 2013




Not indexedb 1 (1)

Outcomesc


ACR 20/30 28 (24)




Pain 53 (45)






Funding 27 (23)






modifications)

52 (44)

Patented 43 (36)




or combined)

15 (13)



11 (9)



10 (8)




Bi Qi capsule 3 (3)




Xiatianwu 3 (3)

Bizhongxiao 2 (2)



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rheumatoid factor.

















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Female 13,697 (72.4)







syndromesa

300 (1.6)


driven)

5,181 (27.4)


Interventions

CHM alone 10,108 (53.4)

CHM + DMARDs 1,595 (8.4)





CHM + NSAIDs 2,101 (11.1)














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bPenicillin.








Quality assessment




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









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bias

Year of

publication

Sample

size

Number of

authors

Language

Funding source


Power calculation

includedb


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


(n = 2).


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22

















CONSORT item

CONSORT

item no. No. (%)


Introduction


Objectives 3 2 (2)

Methods



Outcomes 6 15 (13)

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Randomization






Results








Discussion




Additional analyses










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

















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biases.[154]









the risk of bias tool have larger effect estimates than studies shown to have a low risk of bias.[22]









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.







ACKNOWLEDGMENTS




studies.






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FIGURE LEGENDS



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REFERENCES

1. Cross M, Smith E, Hoy D, et al. The global burden of rheumatoid arthritis: estimates from the

global burden of disease 2010 study. Annals of the rheumatic diseases 2014;73(7):1316-22

doi: 10.1136/annrheumdis-2013-204627published Online First: Epub Date]|.


Chin Med 2011;31(2):152-7


2002;22(2):137-42







First: Epub Date]|.





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30




First: Epub Date]|.




Date]|.










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First: Epub Date]|.















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2010;8(1):35-9



Xi Yi Jie He Za Zhi 2005;25(6):540-2

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2007;27(10):731-4




Ann Intern Med 2009;151(4):229-40, W49-51



2008;36(4):675-83






Epub Date]|.





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Yi Jie He Za Zhi 2010;30(12):1261-4






2002;22(5):359-61



He Za Zhi 2006;26(12):1117-9







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2006;4(2):201-2







2009;29(9):787-90






43

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Clin Ther 2007;29(5):862-73







Zhi 2013;33(5):614-8



Xi Yi Jie He Za Zhi 2001;21(12):895-6






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2012;37(23):3664-6










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2006;26(3):248-50





Med 2004;24(2):83-7








2009;29(11):1023-25






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Epub Date]|.






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100. Xu DS, Tong LM, Qin DH, Yu J, Xu J, Guo J. [Effect of Wudang Zhuifeng Shengshi

Liquor as fumigation bath for ESR, CRP and RF in rheumatoid arthritis]. Hubei Journal of






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2, 27





2014;34(3):276-8



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2004;22(5):39-40






2005;22(6):436-9

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Zhi] 2001;21(12):895



Yi] 2007;28(4):421-2










Rheum 1995;38(1):44-8



1993;20(3):579-81

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证医学杂志 2007(08):601-05



24








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Epub Date]|.











Jama 1995;273(5):408-12

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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


MEDLINE(R), 1946 to June 2015

No. Search terms



3 ra.ti.



6 rheumat*.jw.

7 or/1-6



10 TCM.ti.





infusion*)).mp.





17 or/8-16

18 7 and 17





23 exp PLANT ROOTS/


25 or/19-24


27 chinese.lg.




31 or/26-30

32 25 and 31

33 7 and 32

34 TRIPTERYGIUM/



36 exp PAEONIA/

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38 SAUSSUREA/


40 SINOMENIUM/


42 or/34-41

43 7 and 42




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.



58 Astragal*.mp.

59 Asari*.mp.

60 Notopterygi*.mp.





65 Cinnamom*.mp.

66 Anemarrhen*.mp.


68 Terminali*.mp.

69 Cartham*.mp.

70 or/44-69

71 7 and 70












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104 or/72-103

105 7 and 104
























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131 or/106-130

132 7 and 131






138 Shiguogong*.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


149 147 not 148



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



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 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 2007 [44] 2007 CHN China 1 2 120 ACR RA+TCM guideline (1) University



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


Zhou 2009 [61] 2009 CHN China 1 2 78 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


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)


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


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


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




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


Huang 2002 [105] 2002 CHN China 1 2 59 ACR RA State(City)

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Li 2003 [107] 2003 CHN China 1 2 160


(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


Zeng 2006 [111] 2006 CHN China 1 2 70 ACR RA State(City)


Cai 2006 [113] 2006 CHN China 1 2 90

ACR RA+TCM Sx_no


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


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


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


(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


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)


Ao 2005 [138] 2005 CHN China 1 2 60 ACR RA+TCM guideline (1) University



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)

-


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TITLE


ABSTRACT


4-5

INTRODUCTION



8

METHODS


NA




8-9


Suppl. File


9


9-10


10



10




11

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Page 1 of 2



10


11

RESULTS


12 & Figure 1


12 & Table 1



NA




DISCUSSION


23


25


FUNDING


2



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Journal: BMJ Open

Manuscript ID bmjopen-2016-013242.R2


Date Submitted by the Author: 17-Jan-2017




Rheumatology




BMJ Open on M


http://bmjopen.bm

j.com/

BM


jopen-2016-013242 on 1 March 2017. D

ownloaded from



1




2, Juhee Song

3, Gregory Pratt


2.









[email protected].








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2



Word count: 3,708


Number of tables: 4



SOURCE OF FUNDING




COMPETING INTERESTS









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3







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4

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.


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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5

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.


high-quality evidence is lacking.



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6

STRENGTHS OF THIS STUDY



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













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90%.[15]

















METHODS



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Information sources


















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.






RCTs.












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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






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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






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





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were assessed.


analysis (n = 119).


Duration



Not reported 3 (3)

Year


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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Multicenter 11 (9)

Impact Factor 2013




Not indexedb 1 (1)

Outcomesc


ACR 20/30 28 (24)




Pain 53 (45)






Funding 27 (23)






modifications)

52 (44)

Patented 43 (36)




or combined)

15 (13)



11 (9)



10 (8)




Bi Qi capsule 3 (3)




Xiatianwu 3 (3)

Bizhongxiao 2 (2)



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rheumatoid factor.

















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Female 13,697 (72.4)







syndromesa

300 (1.6)


driven)

5,181 (27.4)


Interventions

CHM alone 10,108 (53.4)

CHM + DMARDs 1,595 (8.4)





CHM + NSAIDs 2,101 (11.1)














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bPenicillin.








Quality assessment




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









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bias

Year of

publication

Sample

size

Number of

authors

Language

Funding source


Power calculation

includedb


Federal/

State Yes No


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


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


(n = 2).


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21

















CONSORT item

CONSORT

item no. No. (%)


Introduction


Objectives 3 2 (2)

Methods



Outcomes 6 15 (13)

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Randomization






Results








Discussion




Additional analyses










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

















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biases.[154]









the risk of bias tool have larger effect estimates than studies shown to have a low risk of bias.[22]









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.







ACKNOWLEDGMENTS




studies.






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FIGURE LEGENDS



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REFERENCES

1. Cross M, Smith E, Hoy D, et al. The global burden of rheumatoid arthritis: estimates from the

global burden of disease 2010 study. Annals of the rheumatic diseases 2014;73(7):1316-22

doi: 10.1136/annrheumdis-2013-204627published Online First: Epub Date]|.


Chin Med 2011;31(2):152-7


2002;22(2):137-42







First: Epub Date]|.





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30




First: Epub Date]|.




Date]|.










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First: Epub Date]|.















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2010;8(1):35-9



Xi Yi Jie He Za Zhi 2005;25(6):540-2

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2007;27(10):731-4




Ann Intern Med 2009;151(4):229-40, W49-51



2008;36(4):675-83






Epub Date]|.





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Yi Jie He Za Zhi 2010;30(12):1261-4






2002;22(5):359-61



He Za Zhi 2006;26(12):1117-9







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2006;4(2):201-2







2009;29(9):787-90






43

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Clin Ther 2007;29(5):862-73







Zhi 2013;33(5):614-8



Xi Yi Jie He Za Zhi 2001;21(12):895-6






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2012;37(23):3664-6










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2006;26(3):248-50





Med 2004;24(2):83-7








2009;29(11):1023-25






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Epub Date]|.






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100. Xu DS, Tong LM, Qin DH, Yu J, Xu J, Guo J. [Effect of Wudang Zhuifeng Shengshi

Liquor as fumigation bath for ESR, CRP and RF in rheumatoid arthritis]. Hubei Journal of






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2, 27





2014;34(3):276-8



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2004;22(5):39-40






2005;22(6):436-9

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Zhi] 2001;21(12):895



Yi] 2007;28(4):421-2










Rheum 1995;38(1):44-8



1993;20(3):579-81

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证医学杂志 2007(08):601-05



24








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Epub Date]|.











Jama 1995;273(5):408-12

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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


MEDLINE(R), 1946 to June 2015

No. Search terms



3 ra.ti.



6 rheumat*.jw.

7 or/1-6



10 TCM.ti.





infusion*)).mp.





17 or/8-16

18 7 and 17





23 exp PLANT ROOTS/


25 or/19-24


27 chinese.lg.




31 or/26-30

32 25 and 31

33 7 and 32

34 TRIPTERYGIUM/



36 exp PAEONIA/

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38 SAUSSUREA/


40 SINOMENIUM/


42 or/34-41

43 7 and 42




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.



58 Astragal*.mp.

59 Asari*.mp.

60 Notopterygi*.mp.





65 Cinnamom*.mp.

66 Anemarrhen*.mp.


68 Terminali*.mp.

69 Cartham*.mp.

70 or/44-69

71 7 and 70












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104 or/72-103

105 7 and 104
























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131 or/106-130

132 7 and 131






138 Shiguogong*.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


149 147 not 148



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



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 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



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







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


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





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



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


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


Hu 2007 [80] 2007 CHN China 1 2 74 ACR RA State(City)



Wang 2001 [83] 2001 CHN China 1 2 322

ACR RA+TCM Sx_no



Zou 2007 [85] 2007 CHN China 1 2 60


(unspecified #) 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


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)


Xu 2005 [100] 2005 CHN China 1 2 200

ACR RA+TCM Sx_no




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


Huang 2002 [105] 2002 CHN China 1 2 59 ACR RA State(City)

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Li 2003 [107] 2003 CHN China 1 2 160


(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


Zeng 2006 [111] 2006 CHN China 1 2 70 ACR RA State(City)


Cai 2006 [113] 2006 CHN China 1 2 90

ACR RA+TCM Sx_no


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


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


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


(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


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)


Ao 2005 [138] 2005 CHN China 1 2 60 ACR RA+TCM guideline (1) University



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


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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)

-


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TITLE


ABSTRACT


4-5

INTRODUCTION



8

METHODS


NA




8-9


Suppl. File


9


9-10


10



10




11

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Page 1 of 2



10


11

RESULTS


12 & Figure 1


12 & Table 1



NA




DISCUSSION


23


25


FUNDING


2



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bmjopen.bmj.comFor peer review only PRISMA 2009 Checklist Page 1 of 2 Section/topic # Checklist item Reported on page # Risk of bias across studies 15 Specify any assessment of risk