(A-011) Potential Bias in Self-Controlled Case Series Design: Impact of Incident vs. Prevalent Scenarios of Exposure and Outcome

Background: The impact of prevalent user and individuals with prior outcomes on bias in self-controlled case series (SCCS) studies has not been thoroughly explored.

Objectives: To evaluate changes in SCCS estimates when applying incident and prevalent exposure and outcome scenarios, and to explore the effects of prevalent user and survivor bias.

Methods: We used the National Health Insurance Service database in South Korea (2002–2015) to conduct two SCCS studies: (1) the risk of retinal detachment following fluoroquinolone use (expected elevated risk), and (2) the risk of acute cardiovascular disease following ranibizumab use (expected null association). Exposure and outcome scenarios were classified based on a washout period of 2 and 1 year, respectively, before the observation period: incident exposure - incident outcome, incident exposure - prevalent outcome, prevalent exposure - incident outcome, and prevalent exposure - prevalent outcome. For each scenario, conditional Poisson regression models, adjusted for time-varying age, estimated incidence rate ratios (IRRs) with 95% confidence intervals (CIs). Sensitivity analyses varied the washout period length.

Results: In the fluoroquinolone study, IRRs of retinal detachment were as follows: 1.83 (95% CI 1.72–1.96) for incident exposure - incident outcome, 1.83 (1.71–1.95) for incident exposure - prevalent outcome, 1.71 (1.62–1.80) for prevalent exposure - incident outcome, and 1.70 (1.62–1.79) for prevalent exposure - prevalent outcome. In the ranibizumab study, IRRs of acute cardiovascular disease were as follows: 0.91 (0.84–0.99) for incident exposure - incident outcome, 0.89 (0.82–0.97) for incident exposure - prevalent outcome, 1.02 (0.94–1.10) for prevalent exposure - incident outcome, and 1.00 (0.93–1.08) for prevalent exposure - prevalent outcome. In the first study, where an increased risk was expected, prevalent exposure scenarios showed IRRs closer to the null, consistent with prevalent user bias. In the second study, where no association was expected, prevalent exposure scenarios resulted in slightly elevated IRRs. However, the direction and magnitude of IRR changes may vary depending on exposure duration and risk periods, reflecting the characteristics of the exposure in each study. Furthermore, although survivor bias was anticipated when varying outcome scenarios, no significant shifts in IRR were observed, possibly due to the high severity of the outcomes, which may lead to a low recurrence rate following exposure.

Conclusions: Potential biases, such as prevalent user bias and survivor bias, should be considered when interpreting SCCS study results. Further quantitative research is needed to better understand the impact of varying exposure and outcome definition on SCCS estimates.