Investigation of design and bias issues in case-control studies of cancer screening using microsimulation
Related Experiment Video
Updated: Oct 9, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
R J Connor1, R Boer, P C Prorok
1Biometry Branch, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892-7354, USA.
Abstract:
Using a microsimulation approach, the authors examined design and bias issues in case-control studies of cancer screening. Specifically, they looked at the impact on the odds ratio of the way in which exposure to screening is defined, the type of age matching, the time scale used, and the criteria used to determine control eligibility. The results showed that defining exposure as "ever/never" screened produced, as expected, a serious bias in favor of screening. Defining exposure as being screened no later than the time the case's cancer is diagnosed has a serious bias against screening. An alternative exposure definition--screening can occur no later than the time the case would have been clinically diagnosed--eliminates the bias against screening. Further, the results showed that the type of age matching and the time scale used can produce a bias against screening and that this bias can be quite strong when case-control studies are performed in populations with a periodic screening program that is the only source of screening. Finally, control eligibility criteria had little effect.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Bias in Epidemiological Studies
Statistical Methods for Analyzing Epidemiological Data
Cancer Survival Analysis