measuring covariate data_presentation (november 14, 2007) 1 measuring covariate data in subsets of...
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Measuring covariate data_Presentation (November 14, 2007) 1
Measuring covariate data in Measuring covariate data in subsets of study populations: subsets of study populations:
Design optionsDesign options
Jean-François Boivin, MD, ScD
McGill University
19 August 2007
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16th International Conference on Pharmacoepidemiology
Barcelona 2000
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What about missing covariate data?
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Do not research that topic
Option #1
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• Conduct study without covariates
• Scientifically reasonable for certain questions
• Example: Sharpe et al. 2000
Option #2
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British Journal of Cancer 2002The effects of tricyclic antidepressants
on breast cancer risk
• Genotoxicity in Drosophila
• Comparison of antidepressants:– 6 genotoxic vs 4 nongenotoxic
• Confounding unlikely
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Option #3
“Confounding by other determinants was studied in analyses with data obtained by interviewing samples of subjects…”
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List 4 - 6 different sampling strategies:
“Confounding by other determinants was studied in analyses with data obtained by interviewing samples of subjects…”
a) ?
b) ?
c) ?
d) ?
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Two-stage sampling
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Entire population (=truth)
OR=0.5
OR=0.5
OR=2.5
Obese
Not obese
All
E+ E-
D+
D+
D+
D-
D-
D-
12,000 140
10,200 10,400
22,200 10,540 32,740
2,000 4010,000 100
200 40010,000 10,000
2,200 44020,000 10,100
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Obese
Not obese
All
E+ E-
D+
D+
D-
D-
22,200 10,540
not available
computerized databases
2,200 44020,000 10,100
D+D-
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Two-stage sampling
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Obese
Not obese
All
E+ E-
250/ 250/250/ 250/ 2,200 440
20,000 10,100
32,740
227 23125 2
23 227125 248
D+D-
D+D-
D+D-
Two-stage sampling
OR1 biased
OR2 biased
250 x 250 250 x 250 = 1
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White. AJE 1982
Walker. Biometrics 1982
Cain, Breslow. AJE 1988
Weinberg, Wacholder. Biometrics 1990
Weinberg, Sandler. AJE 1991
Statistical analysis; further design issues
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Option 1:
Option 2:
Option 3:
Option 4:
No study
No covariate measurement
2-stage sampling
Case only measurement
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Ray et al.Archives of Internal Medicine 1991
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Cyclic antidepressants and the risk of hip fracture
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E+ E-
All
RR=0.5
RR=0.5
RR=
D+D-
D+D-
D+D-
All
Not obese
Obese
RR=0.5
N1=? N2=?
RR=0.5
N3=? N4=?
RR=
RR=0.5
N1=1,000
N2=1,000
RR=0.5
N3=1,000 N4=1,000
RR=0.5
RR=0.5
N1=1,000
N2=1,000 cross-product ratio =1
RR=0.5
N3=1,000 N4=1,000
RR=
RR=0.5
N1=1,000
N2=1,000
RR=0.5
N3=1,000 N4=1,000
RR=
Confounding: Quick review
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Obese
Not obese
All
D+
D+
D+
D-
D-
D-
OR=0.5
OR=0.5
OR=
E+ E-
OR=0.5500 1,500
OR=0.51,000 3,000
OR=
OR=0.5
OR=0.5
OR=0.5
OR=0.5
cross-product ratio =1
OR=0.5
OR=
Case-control study
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Cyclic antidepressants and the risk of hip fracture
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E+ E-
D+Obese
Not obese
All
D-
D+D-
D+D-
2,200 440 computerized database20,000 10,100
22,200 10,540
medical record review
2,200 440 computerized database20,000 10,100
22,200 10,540
2,000 400
? ?
200 40? ?
2,200 44020,000 10,10022,200 10,540
Covariate data on cases only
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E+ E-
D+Obese
Not obese
All
D-
D+D-
D+D-
2,000 400
? ?
200 40? ?
2,200 44020,000 10,10022,200 10,540
OR1
OR2
•assume OR1 = OR2
•then: cross-product ratio =1 implies no confounding
Covariate data on cases only
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What if confounding seems to be present?
Extensions
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Option 1: No study
Option 2: No covariate measurement
Option 3: 2-stage sampling
Option 4: Case only measurements
Suissa, Edwardes. 1997
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Confounder data on cases only
Obese
Not obese
E+ E-
D+D-
2,000 220? ?
200 220? ?
Cross-product ratio =10
Confounding plausible
D+D-
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Epidemiology 1997
• Extensions of Ray’s method to presence of confounding
• Requires additional data from external sources
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Smoker
Nonsmoker
All
E+ E-
D+
D+
D+
D-
D-
D-
Theophylline
17 13 30956 3,154 4,080
14 5 19
3 8 11
14 5 19
24% of 4,080
3 8 11
76% of 4,080
14 5 19
24% of 4,080
obtained from population survey
3 8 11
76% of 4,080
Confounding; no interaction
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• Extensions of Ray’s method to presence of interaction
• Requires further additional data from external sources
Suissa, Edwardes. 1997
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No interaction
OR=0.5
OR=0.5
Obese
Not obese
E+ E-
D+
D+
D-
D-
12,000 140
10,200 10,400
2,000 4010,000 100
200 40010,000 10,000
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Option 1: No study
Option 2: No covariate measurement
Option 3: 2-stage sampling
Option 4: Case only measurements
Suissa, Edwardes. 1997
Multi-stage sampling
Partial questionnaires
Propensity score adjustments
Others:
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Monotone missingness
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Wacholder S, et al.
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Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4
5
6
7
8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3 4
5
6
7
8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4 5
6
7
8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1 2 3
4
5
6
7
8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4
5 6
7
8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4
5
6 7
8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4
5
6
7 8
9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4
5
6
7
8 9
10
…
n
Cov 1 2 3 4 5 6 7 8
Subject 1
2
3
4
5
6
7
8
9 10 …
n
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Wacholder S, et al.
Restricted to a small number of discrete covariates
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Methodologic research
Stürmer et al. AJE 2005, 2007
Propensity score calibration
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• Summarizes information about several covariates into a single number
• Used for matching, stratification, regression
Propensity score
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• Main cohort: selected covariates-“error-prone” scores estimated - regression coefficients estimated
• Sample: additional covariates-gold standard scores-regression calibration
• Advantage: multivariable technique
Stürmer et al. 2005
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“Until the validity and limitation of… [propensity score calibration] have been assessed in different settings, the method should be seen as a sensitivity analysis.”
Stürmer et al. 2005
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Stage 1: 278 cases in 4561 pregnancies
Stage 2: 244 cases + 728 non cases
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“Relatively few examples of two-and three-phase sampling designs for case-control studies have appeared to date in the epidemiologic literature.This is unfortunate, because the stratified designs are easy to implement and can result in substantial savings.”
NE Breslow (2000)
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Consent for second-stage interviews:• Cases: 49%• Controls: 39%
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jean-f.boivin@mcgill.ca
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