Comparison design and evaluation power in cohort and self-controlled case series designs for post-authorization vaccine safety studies

• Published in: PeerJ (San Francisco, CA) Vol. 12; p. e16780
• Main Authors: Sato, Shuntaro, Kawazoe, Yurika, Katsuta, Tomohiro, Fukuda, Haruhisa
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 23.01.2024; PeerJ, Inc; PeerJ Inc
• Subjects: Adverse events; Analysis; Clinical trials; Cohort analysis; Complications and side effects; Hypotheses; Immunization; Medical research; Medicine, Experimental; Post-authorization vaccine safety studies; Power analysis; Public health; Ratios; Self-controlled case series design; Simulation; Statistical analysis; Vaccination; Vaccine development; Vaccines; Power analysis; Post-authorization vaccine safety studies; Self-controlled case series design
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.16780

Post-authorization safety studies (PASSs) of vaccines are important. PASSs enable the evaluation of association between vaccination and adverse events following immunization through common study designs. Clinical trials during vaccine development typically include a few thousand to 10,000 participants while a PASS might aim to detect a few adverse events per 100,000 vaccine recipients. While all available data may be utilized, prior consideration of power analyses are nonetheless crucial for interpretation in cases where statistically significant differences are not found. This research primarily examined cohort study design and self-controlled case series (SCCS) design, estimating the power of a PASS under plausible conditions. Both the cohort study and SCCS designs necessitated large sample sizes or high event counts to guarantee adequate power. The SCCS design is particularly suited to evaluating rare adverse events. However, extremely rare events may not yield sufficient occurrences, thereby resulting in low power. Although the SCCS design can more efficiently control for time-invariant confounding in principle, it solely estimates relative measures. A cohort study design might be preferred if confounding can be adequately managed as it also estimates absolute measures. It may be an easy decision to use all the data at hand for either design. We found it necessary to estimate the sample size and number of events to be used in the study based on information and anticipated results.