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Associations between periodontitis and CHD/Associations between periodontitis and CHD/stroke – how strong is the evidencestroke – how strong is the evidence
Thomas DietrichThomas Dietrich
Boston University School of Dental MedicineBoston University School of Dental Medicine
“old news” 1997
Associated Press, July 9, 1997
Meta-analysis of nine studies on CHD RR= 1.19 (95% CI: 1.08 - 1.32)
rr.5 1 1.5
Combined
DeStephano
Hujoel
Matilla1
Wu_cvd
Morrison
Howell
Joshipura
Beck
Genco
Janket et al., O.O.O. 2003;95:559
Meta-analysis (6 studies) for CHD risk in younger adults (RR = 1.4)
rr.5 1 1.5
Combined
Morrison2
Wu_2
Hujoel2
DeStephano2
Matilla1
Genco
Janket et al., O.O.O. 2003;95:559
Meta-analysis of 5 studies using fatal cardiac events as outcome (RR = 1.5)
rr.5 1 1.5
Combined
Howell_fatal
Hujoel_fatal
Morrison_fatal
Wu_fatal
Beck_fatal
Janket et al., O.O.O. 2003;95:559
Meta-analysis of studies using Stroke/TIA events as outcome
Summary RR = 2.85
95% CI: 1.78 – 4.56Wu et al., Arch Intern Med 2000;160:2749-2755
Beck et al., J Periodontol 1996;67:1123-1137
Janket et al., O.O.O. 2003;95:559
HyperinflammatoryPhenotype
Chronic Periodontitis
CHD
Indirect(e.g. CRP )
Established CVD risk factors
(e.g. smoking, diabetes)
Direct(bacteremia)
Beck et al. 1996, Danesh 1997
Conceptual model
Issues with observational studies
• Issues with epidemiologic studies of periodontitis-CHD association– Exposure measure
• misclassification/measurement error– Self-report vs. clinical measures– Baseline exposure status only
• Conceptualization– (e.g. clinical vs. serological measures)
– Confounding• Residual confounding (smoking)• Unmeasured confounders
– Interpretation• Causal vs. non-causal?
Confounding
Exposure Disease
b+ca+c
c+ddcE -
a+bbaE +
D -D +
?
Relative Risk = Risk exposed / Risk unexposed
RR crude = (a / a+b) / (c / c+d)
Example: Periodontitis and CHD
1000800200
900723177Perio -
1007723Perio +
CHD -CHD +
Relative Risk = Risk exposed / Risk unexposed
RR crude = (a / a+b) / (c / c+d)
10-year cohort study
Baseline: 1000 subjects (10% periodontitis) free of CHD
Example: Periodontitis and CHD
1000800200
900723177Perio -
1007723Perio +
CHD -CHD +
Relative Risk = (23/100) / (177/723)
RR crude = 1.17
Conclusion: Risk for CHD 17% increased if Perio+
10-year cohort study
Baseline: 1000 subjects (10% periodontitis) free of CHD
Example: Periodontitis and CHD
1005050
804040Perio -
201010Perio +
CHD -CHD +
Relative Risk = (10/20) / (40/80)
RR crude = 1.00
Conclusion: no association
What about diabetes?
-10% of cohort had diabetes mellitus at baseline
-For diabetics:
Example: Periodontitis and CHD
900750150
720600120Perio -
18015030Perio +
CHD -CHD +
Relative Risk = (30/180) / (120/720)
RR crude = 1.00
Conclusion: no association
What about diabetes?
-10% of cohort had diabetes mellitus at baseline
-For non-diabetics:
Example: Periodontitis and CHD
Conclusions?
1. 17% increase of risk for Perio+ in entire cohort
2. No increase of risk for Perio+ among diabetics
3. No increase of risk for Perio+ among non-diabetics
What?
Example: Periodontitis and CHD
Answer:
- Diabetes is a confounder (of the Perio/CHD association)
- The crude RR is biased
- There is no independent association between Perio and CHD (independent of diabetes mellitus)
Example: Periodontitis and CHD
1000900100
90082080Perio -
1008020Perio +
DM -DM +
Odds Ratio = (20/80) / (80/820)
OR = 2.56
What about diabetes?
-Association between Periodontitis and Diabetes
Example: Periodontitis and CHD
1000800200
900750150DM -
1005050DM +
CHD -CHD +
Relative Risk = (50/100) / (150/900)
RR = 3.0
What about diabetes?
-Association between Diabetes and CHD
Confounding
• Is a source of bias• Exists because confounder is related to
BOTH the exposure and outcome• can go in either direction
– Crude RR can overestimate true RR– Crude RR can underestimate true RR
Confounding
• What to do about confounding ?
– Randomization (Design)– Matching (Design & Analysis)– Restriction (Design & Analysis)– Adjustment, Stratification (Analysis)
Confounding
Periodontitis CHD
What are important confounders?
Confounder
Confounding
Periodontitis CHD
RR crude is confounded (biased)
Bias depends on:
3. strength of association with exposure
4. strength of association with outcome
5. prevalence of confounder
Smoking
+ +
Smoking !
Confounding
• Residual confounding ?
– Measurement error/misclassification of confounder• Spiekerman et al., J Dent Res 82(5): 345-349, 2003
– Imperfect modeling of confounder• Dietrich et al., J Dent Res 83(11):859-863, 2004
Confounding
Spiekerman et al., J Dent Res 82(5): 345-349, 2003
linear association remaining between mean AL and serum cotinine after adjustment for self-reported intensity (cig/d), age, race and gender (1507 current smokers, NHANES III) .
Confounding
Spiekerman et al., J Dent Res 82(5): 345-349, 2003
• Measurement error/misclassification of confounder– Simulation experiments using joint distribution
of smoking and periodontal variables
– Time to fictional morbid event:t = X•exp(-ß•cotinine/287)
– Cox PH models to estimate association between AL and morbid event (true independent RR = 1)
– Adjustments for self-reported smoking vs. cotinine
Confounding
53.21.0419.81.02self-reported smoking (log cigs/day)
5.21.004.91.00cotininen = 10,000
30.81.0412.71.02self-reported smoking (log cigs/day)
5.11.005.21.00cotininen = 500025%
23.51.058.01.02self-reported smoking (log cigs/day)
4.81.005.11.00cotininen = 10,000
15.01.057.01.02self-reported smoking (log cigs/day)
5.01.004.71.00cotinine (perfecte)n = 50005%
RR=1.9 RR=3.8
CI n variable adjusted RR FP RR FP
Spiekerman et al., J Dent Res 82(5): 345-349, 2003
Confounding• Imperfect modeling of confounder
– Simulation experiments using joint distribution of smoking and periodontal variables
– Time to fictional morbid event:t = X•exp(-ß•CSI)
– Cox PH models to estimate association between AL and morbid event (true independent RR = 1)
– Adjustments for self-reported smoking vs. cotinine
Confounding
1.40.961.50.961.60.96
1.60.961.80.962.20.97
1.60.961.50.962.80.98
7.11.095.21.053.91.01
111.148.21.115.71.06
551.41511.38421.34
FPHRFPHRFPHR
10 yrs
5 yrs1 yrτ
Crude model (no adjustment for smoking)
Confounding
1.40.961.50.961.60.96
1.60.961.80.962.20.97
1.60.961.50.962.80.98
7.11.095.21.053.91.01
111.148.21.115.71.06
551.41511.38421.34
FPHRFPHRFPHR
10 yrs
5 yrs1 yrτ
Never, former, current
Confounding
1.40.961.50.961.60.96
1.60.961.80.962.20.97
1.60.961.50.962.80.98
7.11.095.21.053.91.01
111.148.21.115.71.06
551.41511.38421.34
FPHRFPHRFPHR
10 yrs
5 yrs1 yrτ
Never, Former, Current 0 – 10 /d, 11 – 20 /d, > 20 /d
Confounding
1.40.961.50.961.60.96
1.60.961.80.962.20.97
1.60.961.50.962.80.98
7.11.095.21.053.91.01
111.148.21.115.71.06
551.41511.38421.34
FPHRFPHRFPHR
10 yrs
5 yrs1 yrτ
packyears / former, current, intensity, duration / CSI (perfect)
Bias due to misclassification of periodontitis
• AL and PD of mesiobuccal sites from 12,976 subjects in NHANES III• Bootstrap samples (n=5000)• time to fictional morbid events: t = X * exp (-ln(1.5) * AL)
– X : exponential random variable– AL: mean AL per subject– RR of morbid event for an increase in mean AL of 1 mm was 1.5
• fixed censoring time was chosen to yield a cumulative incidence of 5%
• Periodontal disease defined using three previously used criteria: – (1) at least 1 site with PD 4 mm– (2) at least 4 sites with PD 4 mm– (3) at least 1 site with PD 6 mm.
• randomly misclassified periodontal disease variables• Cox PH regression models, median HR of 1000 repetitions• relative bias: 1-(ln HRm /ln HRp)
Bias due to misclassification of periodontitis
1.61/55%1.28/59% 1.53/14%90%100%
2.90/0.0%1.80/1.8 % 1.63/1.2% 100%90%
1.55/59%1.26/61%1.49/19%90%90%
2.9/-1.82/-1.64/-100%100%
1+ PD6+
HR / Bias
4+ PD4+
HR / Bias
1+ PD4+
HR / Bias
SPECSENS
Bias due to misclassification of periodontitis
1.35/72%1.16/75%1.43/28%80%100%
2.87/1.0%1.80/1.8%1.58/7.5%100%80%
1.26/78%1.12/81%1.32/44%80%80%
2.9/-1.82/-1.64/-100%100%
1+ PD6+
HR / Bias
4+ PD4+
HR / Bias
1+ PD4+
HR / Bias
SPECSENS
Bias due to misclassification of periodontitis
1.16/86%1.07/89%1.17/68%90%30%
1.37/70%1.18/72%1.34/41%90%60%
1.09/92%1.04/94%1.12/77%80%40%
2.9/-1.82/-1.64/-100%100%
1+ PD6+
HR / Bias
4+ PD4+
HR / Bias
1+ PD4+
HR / Bias
SPECSENS
Meta-analysis of nine studies on CHD RR= 1.19 (95% CI: 1.08 - 1.32)
rr.5 1 1.5
Combined
DeStephano
Hujoel
Matilla1
Wu_cvd
Morrison
Howell
Joshipura
Beck
Genco
Janket et al., O.O.O. 2003;95:559
New Epidemiologic Studies
• Case control study• 303 incident cases of acute cerebral ischemia• 300 population controls• 168 hospital controls• Periodontal status assessed clinically and
radiographically• periodontal probing at 4 sites in all teeth• Subjects were categorized into 4 categories based on
means clinical attachment levels (CAL), which allowed evaluation of the dose-response pattern.
Grau et al., Stroke 2004
Grau et al., Stroke 2004
1 a SR with homogeneity of RCTs b Individual RCT with narrow Confidence Interval c All or none
2 a SR with homogeneity of cohort studies b Individual cohort study (including low quality RCT; e.g., <80% follow-up) c "Outcomes" Research; Ecological studies
3 a SR with homogeneity of case-control studies b Individual Case-Control Study
12 Case-series and poor quality cohort and case-control studies
13 Expert opinion without explicit critical appraisal, or based on physiology, bench research or "first principles"
Hierarchy (levels) of evidence
Efficacy of AB for secondary CVD prevention: major RCT
• antibiotic arm of the PROVE-IT trial• Inclusion: patients with an acute coronary syndrome• randomized to placebo (n=2,086) or monthly courses of
gatifloxacin (n=2,076) • 2 year follow-up• composite primary endpoint (death, MI, unstable AP,
revascularization, stroke) • cum. Incidence: placebo: 25.1%; treatment: 23.7%• Stratification by baseline CRP:
– CRP above median: placebo: 24.9%; treatment: 25.2%– CRP below median: placebo: 21.6%; treatment: 24.4%
• no other subgroup could be identified in which the treatment was effective
Cannon et al., New Engl J Med 2005
Efficacy of AB for secondary CVD prevention: major RCT
• Inclusion: patients with documented stable CHD• Randomiyed to placebo (n=2,008) or 600mg azithromycin once per
week for a year (n=2,004)• Patients followed for up to 4.5 years • composite primary endpoint (fatal MI, revascularization, unstable
AP)• Cumulative incidence identical: placebo: 22.4%; treatment: 22.3%• Conclusion: no clinically significant benefit in the secondary
prevention of CHD events from one year of weekly azithromycin treatment
• neither Chlamydia pneumoniae nor another organism susceptible to azithromycin plays an important role in the pathogenesis of CHD events in subjects with advanced CHD.
Grayston et al., New Engl J Med 2005
Hill’s Criteria for Causality
• Strength • Consistency• Specificity• Temporality• Biologic gradient• Biologic plausibility • Experimental evidence
A.B. Hill (1965) “The environment and disease: association or causation? Proc. Roy. Soc. Med. 58:295-300.
Hill’s Criteria for Causalityvs. EBM levels of evidence
• Can RCT prove causality?– Proof of what?– Theoretically? – Practically? (feasibility)
• Clinical study of PD patients (n=30) and healthy controls (n=31), matched for age, sex and cardiovascular risk factors
• Flow-mediated dilation (FMD) of brachial artery• Periodontal treatment: SC/RP, CHX (14 days), systemic antibiotics
(7 days: Augmentin, metronidazole)• Measures at baseline and at 3-month f/u• Perio tx improved FMD and lowered CRP
Periodontal treatment improves endothelial dysfunction in patients with
severe periodontitisG Seinost et al Am Heart J 2005; 149:1050-1054
Periodontal treatment improves endothelial dysfunction in patients with severe periodontitis
G Seinost et al Am Heart J 2005; 149:1050-1054
Tonetti et al., Treatment of Periodontitis and Endothelial Function
N Engl J Med 2007; 356:911-920.
Tonetti et al., Treatment of Periodontitis and Endothelial Function
N Engl J Med 2007; 356:911-920.
Periodontitis and age-related risk of Periodontitis and age-related risk of coronary heart disease in mencoronary heart disease in men
T. DietrichT. Dietrich11, M. Jimenez*, M. Jimenez*1,2,31,2,3, E.A. Krall, E.A. Krall11, , P.S. VokonasP.S. Vokonas44, R.I. Garcia, R.I. Garcia1,41,4
1 1 Boston University School of Dental MedicineBoston University School of Dental Medicine
2 2 Harvard School of Dental Medicine Harvard School of Dental Medicine 3 3 Harvard School of Public HealthHarvard School of Public Health
4 4 VA Boston Healthcare SystemVA Boston Healthcare System
Objective
• Evaluate strength of periodontitis-CHD association in long-term cohort study– Clinical measures of periodontal disease over
time– Time-varying effects of exposure and
potential confounders
MethodsMethods
• PopulationPopulation
– 1,231 male participants of both the Veterans’ Affairs Normative Aging (NAS) and Dental Longitudinal Study (DLS)
– DLS began in 1968– men are not VA patients– medical/dental exams every 3 years
• Outcomes:Outcomes: – Physician diagnosed CHD (MI, angina pectoris)
• ECG, biomarkers, history– fatal CHD
• ICD-8 410-414, primary cause of death
MethodsMethods
• Exposure:Exposure: (dental exam every 3 yr)– Full mouth radiographs
• Bone loss (Schei score) assessed by single reader (0-5 in 20% increments)
• Mean per subject bone loss score
– Probing pocket depth (PD)• calibrated examiners• Maximum PD per tooth recorded as score
(0-3 mm, >3-5 mm, >5 mm)• Cumulative PD calculated as sum of max. PD of all present teeth
– Edentulism
MethodsMethods
Exclusions:• participant with prevalent CHD at DLS baseline
Potential confounders assessed: • Baseline: Age, education & occupation • Time-varying effects of:
– Smoking: using a comprehensive smoking index (Dietrich & Hoffmann 2004)
– Body mass index (BMI) – Cholesterol:
• Total cholesterol & High density lipoprotein cholesterol (HDL) – Triglycerides– Hypertension – Blood Pressure:
• mean systolic & mean diastolic separately – Diabetes: Diagnosis of diabetes, fasting glucose level, 2 hour glucose
level– Alcohol consumption
MethodsMethods
Statistical analysis:• Cox PH regression with time-varying covariates• Time from baseline until
– CHD event (total or fatal)– loss to follow-up– last NAS exam
• Age-adjusted and multivariate adjusted (“kitchen sink”) models• Models stratified by age (< 50, 50+ years)
Results
17%8%5% Edentulous
63%74%78% >20
Number of teeth
19%20%23%Alcohol Use
24%22%25%Smokers
10%7%6%Diabetes
77.6 ± 9.977.7 ± 9.176.1 ± 8.8Diastolic Blood Pressure
131.1 ± 19.1126.8 ± 16.0122.8 ± 14.8Systolic Blood Pressure
17%14%10%Hypertension
178.1 ± 129.9168.6 ± 114.3147.8 ± 66.1Triglycerides
42.1 ± 11.8945.7 ± 14.449.4 ± 13.7HDL
235.2 ± 48.9232.9 ± 51.8220.7 ± 44.38Total Cholesterol
26.4 ± 3.426.5 ± 3.226.0 ± 3.0BMI
55 ± 9.950 ± 8.948 ± 9.3Age
109364839 N
Fatal CHDCHDNon-CHD
Baseline characteristics by CHD
Fatal & non-fatal CHD – bone loss
p=0.91p=0.87 Trend
p=0.02p=0.001 Trend
1.0 (Reference)1.0 (Reference)37260.30- 0.5
1.0 (Reference)1.0 (Reference)52270.24- 0.5
0.9 (0.6, 1.4)1.0 (0.6, 1.5)47240.75>0.5 – 1
0.9 (0.6, 1.5)1.1 (0.7, 1.6)43211.21> 1 - 1.5
1.1 (0.7, 1.8)1.2 (0.7, 1.9)30151.90> 1.5
1.6 (0.9, 2.8)1.9 (1.1, 3.2)260-Edentulous
50+ years
1.3 (0.6, 2.8)1.5 (0.7, 3.1)80-Edentulous
1.7 (1.1, 2.8)2.0 (1.3, 3.3)26181.81> 1.5
1.6 (1.1, 2.5)1.8 (1.2, 2.8)35221.21> 1 - 1.5
1.5 (1.0, 2.2)1.6 (1.1, 2.3)60250.73>0.5 – 1
< 50 years
Multivariate
HR (95% CI)Age Adjusted HR (95% CI)# events# teethMedianBL Score
Fatal & non-fatal CHD – bone loss
0
0.5
1.0
1.5
2.0
2.5
3.0
0.3 0.7 1.3 1.9edentulous
< 50 years 50+ years
mean bone loss score [mm]
HR
(95
% C
I)
Fatal CHD – bone loss
0
1
2
3
4
5
0.3 0.8 1.2 1.9edentulous
mean bone loss score [mm]
HR
(95
% C
I)
50+ years
Fatal & non-fatal CHD – cumulative PD
p=0.54p=0.94 Trend
p=0.002p=0.001 Trend
1.0 (Reference)1.0 (Reference)442300
1.0 (Reference)1.0 (Reference)452400
1.1 (0.7, 1.7)1.2 (0.8, 1.9)4822124 – 20
1.4 (0.9, 2.1)1.6 (1.0, 2.4)44233020 – 40
0.8 (0.5, 1.4)1.0 (0.6, 1.7)20246040 - 164
1.7 (1.0, 2.9)2.1 (1.3, 3.5)260-Edentulous
50+ years
1.2 (0.6, 2.6)1.3 (0.6, 2.8)80-Edentulous
1.6 (1.0, 2.4)1.7(1.1, 2.6)43266040 - 164
1.2 (0.8, 2.0)1.2 (0.8, 1.9)32263020 – 40
1.3 (0.9, 2.0)1.3 (0.9, 2.0)5125124 – 20
< 50 years
Multivariate
HR (95% CI)Age Adjusted HR (95% CI)# events# teethMedianCum. PD
0
0.5
1.0
1.5
2.0
2.5
3.0
0 12 30 60edentulous
mean cumulative PD [mm]
Fatal & non-fatal CHD – cumulative PDH
R (
95%
CI)
< 50 years 50+ years
Discussion / Conclusions
• Moderate association between periodontitis and CHD among younger men only
• Consistent evidence for effect-modification by age• DeStefano, BMJ 1993• Geismar, J Periodontol 2006• Indirect evidence
• Feasibility of RCT?• Association between edentulism and CHD among older
men• Mean bone loss vs. cumulative PD: similar results• Common pro-inflammatory phenotype may be important
(dominant) component of observed association
HyperinflammatoryPhenotype
Chronic Periodontitis
CHD
Indirect(e.g. CRP )
Established CVD risk factors
(e.g. smoking, diabetes)
Direct(bacteremia)
Beck et al. 1996, Danesh 1997
Directed acyclic graph
Acknowledgements
NIDCR GrantsNIDCR Grants: R03 DE016357 K24 DE00419
T14 DE017284
US Dept. of Veterans' AffairsUS Dept. of Veterans' Affairs