Measuring covariate data in subsets of study populations design options
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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

Jean-François Boivin, MD, ScD

McGill University

19 August 2007

Measuring covariate data_Presentation (November 14, 2007)


16th International Conference on Pharmacoepidemiology

Barcelona 2000


What about missing covariate data?


Option #1

Do not research that topic


Option #2

  • Conduct study without covariates

  • Scientifically reasonable for certain questions

  • Example: Sharpe et al. 2000


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


Option #3

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


“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) ?


Two-stage sampling


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


E+

E-

Obese

D+

D-

not available

Not obese

D+

D-

All

computerized databases

D+

D-

22,200

10,540


Two-stage sampling


Two-stage sampling

E+

E-

Obese

D+

OR1biased

D-

Not obese

D+

OR2 biased

D-

All

D+

250 x250250 x250

= 1

D-


Statistical analysis; further design issues

White. AJE 1982

Walker. Biometrics 1982

Cain, Breslow. AJE 1988

Weinberg, Wacholder. Biometrics 1990

Weinberg, Sandler. AJE 1991


Option 1:

Option 2:

Option 3:

Option 4:

No study

No covariate measurement

2-stage sampling

Case only measurement


Ray et al.

Archives of Internal Medicine 1991


Cyclic antidepressants and the risk of hip fracture


Confounding: Quick review

E+

E-

Obese

D+

D-

Not obese

D+

D-

All

All

D+

D-


Case-control study

E+

E-

Obese

D+

D-

Not obese

D+

D-

All

D+

D-


Cyclic antidepressants and the risk of hip fracture


Covariate data on cases only

E+

E-

Obese

D+

D-

Not obese

D+

D-

All

D+

D-


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-


Extensions

What if confounding seems to be present?


Option 1: No study

Option 2: No covariate measurement

Option 3: 2-stage sampling

Option 4: Case only measurements

Suissa, Edwardes. 1997


Confounder data on cases only

E+

E-

Obese

D+

D-

Not obese

D+

D-

Cross-product ratio =10

Confounding plausible


Epidemiology 1997

  • Extensions of Ray’s method to presence of confounding

  • Requires additional data from external sources


Confounding; no interaction

Theophylline

E+

E-

Smoker

D+

D-

Nonsmoker

D+

D-

All

D+

D-


Suissa, Edwardes. 1997

  • Extensions of Ray’s method to presence of interaction

  • Requires further additional data from external sources


No interaction

E+

E-

Obese

D+

OR=0.5

D-

12,000

140

Not obese

D+

OR=0.5

D-

10,200

10,400


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


Monotone missingness


Wacholder S, et al.


Wacholder S, et al.

Restricted to a small number of discrete covariates


Methodologic research

Stürmer et al. AJE 2005, 2007

Propensity score calibration


Propensity score

  • Summarizes information about several covariates into a single number

  • Used for matching, stratification, regression


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


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.”


Stage 1: 278 cases in 4561 pregnancies

Stage 2: 244 cases + 728 non cases


“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)


  • Consent for second-stage interviews:

  • Cases: 49%

  • Controls: 39%


jean-f.boivin@mcgill.ca


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