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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. 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

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  1. 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)

  2. 16th International Conference on Pharmacoepidemiology Barcelona 2000

  3. What about missing covariate data?

  4. Option #1 Do not research that topic

  5. Option #2 • Conduct study without covariates • Scientifically reasonable for certain questions • Example: Sharpe et al. 2000

  6. 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

  7. Option #3 “Confounding by other determinants was studied in analyses with data obtained by interviewing samples of subjects…”

  8. “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) ?

  9. Two-stage sampling

  10. 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

  11. E+ E- Obese D+ D- not available Not obese D+ D- All computerized databases D+ D- 22,200 10,540

  12. Two-stage sampling

  13. Two-stage sampling E+ E- Obese D+ OR1biased D- Not obese D+ OR2 biased D- All D+ 250 x250250 x250 = 1 D-

  14. Statistical analysis; further design issues White. AJE 1982 Walker. Biometrics 1982 Cain, Breslow. AJE 1988 Weinberg, Wacholder. Biometrics 1990 Weinberg, Sandler. AJE 1991

  15. Option 1: Option 2: Option 3: Option 4: No study No covariate measurement 2-stage sampling Case only measurement

  16. Ray et al. Archives of Internal Medicine 1991

  17. Cyclic antidepressants and the risk of hip fracture

  18. Confounding: Quick review E+ E- Obese D+ D- Not obese D+ D- All All D+ D-

  19. Case-control study E+ E- Obese D+ D- Not obese D+ D- All D+ D-

  20. Cyclic antidepressants and the risk of hip fracture

  21. Covariate data on cases only E+ E- Obese D+ D- Not obese D+ D- All D+ D-

  22. 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-

  23. Extensions What if confounding seems to be present?

  24. Option 1: No study Option 2: No covariate measurement Option 3: 2-stage sampling Option 4: Case only measurements Suissa, Edwardes. 1997

  25. Confounder data on cases only E+ E- Obese D+ D- Not obese D+ D- Cross-product ratio =10 Confounding plausible

  26. Epidemiology 1997 • Extensions of Ray’s method to presence of confounding • Requires additional data from external sources

  27. Confounding; no interaction Theophylline E+ E- Smoker D+ D- Nonsmoker D+ D- All D+ D-

  28. Suissa, Edwardes. 1997 • Extensions of Ray’s method to presence of interaction • Requires further additional data from external sources

  29. No interaction E+ E- Obese D+ OR=0.5 D- 12,000 140 Not obese D+ OR=0.5 D- 10,200 10,400

  30. 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

  31. Monotone missingness

  32. Wacholder S, et al.

  33. Wacholder S, et al. Restricted to a small number of discrete covariates

  34. Methodologic research Stürmer et al. AJE 2005, 2007 Propensity score calibration

  35. Propensity score • Summarizes information about several covariates into a single number • Used for matching, stratification, regression

  36. 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

  37. 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.”

  38. Stage 1: 278 cases in 4561 pregnancies Stage 2: 244 cases + 728 non cases

  39. “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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