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Measuring covariate data in subsets of study populations: Design options. Jean-François Boivin, MD, ScD McGill University 19 August 2007. 16 th International Conference on Pharmacoepidemiology Barcelona 2000. What about missing covariate data?. Option #1. Do not research that topic.

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measuring covariate data in subsets of study populations design options

Measuring covariate data in subsets of study populations: Design options

Jean-François Boivin, MD, ScD

McGill University

19 August 2007

Measuring covariate data_Presentation (November 14, 2007)

slide5
Option #1

Do not research that topic

slide6
Option #2
  • Conduct study without covariates
  • Scientifically reasonable for certain questions
  • Example: Sharpe et al. 2000
british journal of cancer 2002 the effects of tricyclic antidepressants on breast cancer risk
British Journal of Cancer2002The effects of tricyclic antidepressants on breast cancer risk
  • Genotoxicity in Drosophila
  • Comparison of antidepressants:
    • 6 genotoxic vs 4 nongenotoxic
  • Confounding unlikely
slide8
Option #3

“Confounding by other determinants was studied in analyses with data obtained by interviewing samples of subjects…”

slide9
“Confounding by other determinants was studied in analyses with data obtained by interviewing samples of subjects…”

List 4 - 6 different sampling strategies:

a) ?

b) ?

c) ?

d) ?

slide13
Entire population (=truth)

E+

E-

Obese

D+

OR=0.5

D-

12,000

140

Not obese

D+

OR=0.5

D-

10,200

10,400

All

D+

OR=2.5

D-

22,200

10,540

32,740

slide14
E+

E-

Obese

D+

D-

not available

Not obese

D+

D-

All

computerized databases

D+

D-

22,200

10,540

slide16
Two-stage sampling

E+

E-

Obese

D+

OR1biased

D-

Not obese

D+

OR2 biased

D-

All

D+

250 x250250 x250

= 1

D-

slide17
Statistical analysis; further design issues

White. AJE 1982

Walker. Biometrics 1982

Cain, Breslow. AJE 1988

Weinberg, Wacholder. Biometrics 1990

Weinberg, Sandler. AJE 1991

slide19
Option 1:

Option 2:

Option 3:

Option 4:

No study

No covariate measurement

2-stage sampling

Case only measurement

slide20
Ray et al.

Archives of Internal Medicine 1991

slide22
Confounding: Quick review

E+

E-

Obese

D+

D-

Not obese

D+

D-

All

All

D+

D-

slide23
Case-control study

E+

E-

Obese

D+

D-

Not obese

D+

D-

All

D+

D-

slide25
Covariate data on cases only

E+

E-

Obese

D+

D-

Not obese

D+

D-

All

D+

D-

slide26
Covariate data on cases only

E+

E-

Obese

D+

D-

Not obese

D+

D-

  • assumeOR1= OR2
  • then: cross-product ratio=1 implies no confounding

All

D+

D-

slide27
Extensions

What if confounding seems to be present?

slide29
Option 1: No study

Option 2: No covariate measurement

Option 3: 2-stage sampling

Option 4: Case only measurements

Suissa, Edwardes. 1997

slide30
Confounder data on cases only

E+

E-

Obese

D+

D-

Not obese

D+

D-

Cross-product ratio =10

Confounding plausible

slide31
Epidemiology 1997
  • Extensions of Ray’s method to presence of confounding
  • Requires additional data from external sources
slide32
Confounding; no interaction

Theophylline

E+

E-

Smoker

D+

D-

Nonsmoker

D+

D-

All

D+

D-

slide33
Suissa, Edwardes. 1997
  • Extensions of Ray’s method to presence of interaction
  • Requires further additional data from external sources
slide34
No interaction

E+

E-

Obese

D+

OR=0.5

D-

12,000

140

Not obese

D+

OR=0.5

D-

10,200

10,400

slide35
Option 1: No study

Option 2: No covariate measurement

Option 3: 2-stage sampling

Option 4: Case only measurements

Suissa, Edwardes. 1997

Others:

Multi-stage sampling

Partial questionnaires

Propensity score adjustments

slide41
Wacholder S, et al.

Restricted to a small number of discrete covariates

slide42
Methodologic research

Stürmer et al. AJE 2005, 2007

Propensity score calibration

slide43
Propensity score
  • Summarizes information about several covariates into a single number
  • Used for matching, stratification, regression
slide44
Stürmer et al. 2005
  • Main cohort: selected covariates

- “error-prone” scores estimated

- regression coefficients estimated

  • Sample: additional covariates

- gold standard scores

- regression calibration

  • Advantage: multivariable technique
slide45
Stürmer et al. 2005

“Until the validity and limitation of… [propensity score calibration] have been assessed in different settings, the method should be seen as a sensitivity analysis.”

slide48
Stage 1: 278 cases in 4561 pregnancies

Stage 2: 244 cases + 728 non cases

slide50
“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)

slide51
Consent for second-stage interviews:
  • Cases: 49%
  • Controls: 39%
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