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Adverse Effects of Observational Studies When Examining Adverse Outcomes of Drugs

Case-Control Studies with Low Prevalence of Exposure

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Abstract

Objectives: The case-control study is commonly used to examine adverse drug events, in which prevalence of exposure in the source population is frequently very low. The objective of the current study was to examine the bias inherent in the odds ratio assessing the association between exposure and an adverse outcome when prevalence of exposure in the source population is extremely low.

Design: Monte Carlo simulations examined the effect of sample size, exposure prevalence, and magnitude of the underlying odds ratio on the bias of the estimated risk ratio, and the power to detect a non-zero risk ratio.

Results: Once the underlying odds ratio was at least four, the adverse effects of low prevalence of exposure was minimal. Studies with small sample sizes and low prevalence of exposure, coupled with small to moderate effect sizes, can result in biased estimates of association between exposure and disease status. With a sample size of 200 and an exposure prevalence of 0.5% in the control population, the bias in the estimated odds ratio can be as large as 115%. However, bias becomes negligible as sample size becomes large (n ≥ 2000), even when prevalence of exposure is very low. Once the expected number of exposed controls is at least eight, the bias in the estimated odds ratio was no more than 5%.

Conclusions: Studies with small sample sizes and low prevalence of exposure, coupled with small to moderate effect sizes can result in biased estimates of association between exposure status and adverse drug effects. However, bias becomes negligible as sample size becomes large.

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References

  1. Rothman KJ, Greenland S. Modern epidemiology. New York: Lippincott Williams & Wilkins, 1998

    Google Scholar 

  2. Breslow NE, Day NE. Statistical methods in cancer research. vol 1: the analysis of case-control studies. Lyon: IARC, 1980

    Google Scholar 

  3. Roujeau JC, Kelly JP, Naldi L, et al. Medication use and the risk of Stevens-Johnson syndrome or toxic epidermal necrolysis. N Engl J Med 1995; 333: 1600–7

    Article  PubMed  CAS  Google Scholar 

  4. Kernan WN, Viscoli CM, Brass LM, et al. Phenylpropanolamine and the risk of hemorrhagic stroke. N Engl J Med 2000; 343: 1826–32

    Article  PubMed  CAS  Google Scholar 

  5. Abenhaim L, Moride Y, Brenot F, et al. Appetite-suppressant drugs and the risk of primary pulmonary hypertension. N Engl J Med 1996; 335: 609–16

    Article  PubMed  CAS  Google Scholar 

  6. Zornberg GL, Jick H. Antipsychotic drug use and the risk of first-time idiopathic venous thromboembolism: a case-control study. Lancet 2000; 356: 1219–23

    Article  PubMed  CAS  Google Scholar 

  7. International Agranulocytosis and Aplastic Anaemia Study. Risk of agranulocytosis and aplastic anaemia in relation to use of antithyroid drugs. BMJ 1988; 297: 262–5

    Google Scholar 

  8. Rawson NSB, Rutledge Harding S, Malcolm E, et al. Hospitalizations for aplastic anemia and agranulocytosis in Saskatchewan: incidence and associations with antecedent prescription drug use. J Clin Epidemiol 1998; 51: 1343–55

    Article  PubMed  CAS  Google Scholar 

  9. Kelly JP, Kaufman DW, Shapiro S. Risks of agranulocytosis and aplastic anemia in relation to the use of cardiovascular drugs: the International Agranulocytosis and Aplastic Anemia Study. Clin Pharmacol Ther 1991; 49: 330–41

    Article  PubMed  CAS  Google Scholar 

  10. Pastuszak AL, Schuler L, Speck-Martins CE, et al. Use of misoprostol during pregnancy and mobius’ syndrome in infants. N Engl J Med 1998; 338: 1881–5

    Article  PubMed  CAS  Google Scholar 

  11. Jick H. The discovery of drug-induced illness. N Engl J Med 1977; 296: 481–5

    Article  PubMed  CAS  Google Scholar 

  12. de Abajo FJ, Rodriguez LAG, Montero D. Association between selective serotonin reuptake inhibitors and upper gastrointestinal bleeding: population-based case-control study. BMJ 1999; 319: 1106–9

    Article  PubMed  Google Scholar 

  13. Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996; 49: 1373–9

    Article  PubMed  CAS  Google Scholar 

  14. Peduzzi P, Concato J, Feinstein AR, et al. Importance of events per independent variable in proportional hazards regression analysis II: accuracy and precision of regression estimates. J Clin Epidemiol 1995; 48: 1503–10

    Article  PubMed  CAS  Google Scholar 

  15. Becker S. A comparison of maximum likelihood and jewell’s estimators of the odds ratio and relative risk in single 2x2 tables. Stat Med 1989; 8: 987–96

    Article  PubMed  CAS  Google Scholar 

  16. Walter SD, Cook RJ. A comparison of several point estimators of the odds ratio in a single 2 × 2 contingency table. Biometrics 1991; 47: 795–811

    Article  PubMed  CAS  Google Scholar 

  17. Haldane JBS. The estimation and significance of the logarithm of a ratio of frequencies. Ann Hum Genet 1956; 20: 309–11

    Article  PubMed  CAS  Google Scholar 

  18. Jewel NP. On the bias of commonly used measures of association for 2 × 2 tables. Biometrics 1986; 42: 351–8

    Article  Google Scholar 

  19. Gart JJ, Zweifel JR. On the bias of various estimators of the logit and its variance with application to quantal bioassay. Biometrika 1967; 54: 181–7

    PubMed  CAS  Google Scholar 

  20. Greenland S, Schwartzbaum JA, Finkle WD. Problems due to small samples and sparse data in conditional logistic regression analysis. Am J Epidemiol 2000; 151: 531–9

    Article  PubMed  CAS  Google Scholar 

  21. Breslow NE, Day NE. Statistical methods in cancer research, vol II: the analysis of cohort studies. Lyon: IARC, 1987

    Google Scholar 

  22. Mathsoft Inc. S-Plus, version 5.1. 1999

  23. SAS Institute Inc. SAS, version 6.12. Cary (NC), 1999

  24. Doll R, Hill AB. Smoking and carcinoma of the lung: preliminary report. BMJ 1950; II: 739–48

    Article  Google Scholar 

  25. Psaty BM, Koepsell TD, LoGerfo JP, et al. Beta-blockers and primary prevention of coronary heart disease in patients with high blood pressure. JAMA 1989; 261: 2087–94

    Article  PubMed  CAS  Google Scholar 

  26. Hu S, Hertz-Picciotto I, Siemiatycki J. When to be skeptical of negative studies: pitfalls in evaluating occupational risks using population-based case-control studies. Can J Public Health 1999; 90: 138–42

    PubMed  CAS  Google Scholar 

  27. Lee-Feldstein A. A comparison of several measures of exposure to arsenic: matched case-control study of copper smelter employees. Am J Epidemiol 1989; 129: 112–24

    PubMed  CAS  Google Scholar 

  28. Jarup L, Pershagen G. Arsenic exposure, smoking, and lung cancer in smelter workers: a case-control study. Am J Epidemiol 1991; 134: 545–51

    PubMed  CAS  Google Scholar 

  29. Czeizel AE, Rockenbauer M, Sorenson HT, et al. A population-based case-control teratologic study of furazidine, a nitrofuranderivative treatment during pregnancy. Clin Nephrol 2000; 53: 257–63

    PubMed  CAS  Google Scholar 

  30. Thomas DG. Exact confidence intervals for the odds ratio in a 2x2 table. Appl Stat 1971; 10: 105–10

    Article  Google Scholar 

  31. Stata Corporation. Stata 7.0. Texas: College Station, 2001

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Acknowledgements

The study was funded by the Institute for Clinical Evaluative Sciences. The funding arrangement allowed the authors freedom to design, analyse, and publish the results.

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Correspondence to Peter C. Austin.

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Austin, P.C., Mamdani, M. & Williams, I.J. Adverse Effects of Observational Studies When Examining Adverse Outcomes of Drugs. Drug-Safety 25, 677–687 (2002). https://doi.org/10.2165/00002018-200225090-00006

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