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Related Experiment Videos

Bias in case-control studies of screening effectiveness

R S Hosek1, W D Flanders, A J Sasco

  • 1Emory University School of Public Health, Division of Epidemiology, Atlanta, GA 30329, USA.

American Journal of Epidemiology
|January 15, 1996
PubMed
Summary

Case-control studies assessing screening program effectiveness may be biased. Including the diagnostic exam in exposure history creates positive bias, while excluding it causes negative bias, affecting cancer screening results.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Screening programs aim to reduce chronic disease mortality and morbidity.
  • Matched case-control studies are common for evaluating screening program effectiveness due to simplicity and cost.
  • Methodological evaluations of case-control study validity in this context are lacking.

Purpose of the Study:

  • To investigate potential bias in case-control studies evaluating screening programs.
  • To assess the impact of specific design rules on the validity of odds ratio calculations.
  • To explore how exposure history definition influences study outcomes.

Main Methods:

  • Development of a simple deterministic model simulating cohort screening and disease patterns.
  • Selection of matched cases and controls from the simulated cohort.

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  • Calculation of odds ratios using screening histories, mimicking standard practice.

    • Main Results:

    • Systematic inclusion of the diagnostic examination in exposure history leads to positive bias (OR > 1) even without a true effect.
    • Systematic exclusion of the diagnostic examination results in negative bias (OR < 1).
    • The findings suggest commonly used case-control methods may produce biased odds ratios.

    Conclusions:

    • Standard case-control study designs for screening program evaluation may introduce significant bias.
    • Bias can occur regardless of the actual effectiveness of the screening program.
    • Alternative methods for defining exposure intervals may be necessary to mitigate bias.