Retrospective Cohort Study

Both designs use existing data, but they differ in sampling logic. A retrospective cohort study starts with an exposed group and an unexposed group and compares outcome incidence between them; it yields relative risks and incidence rates. A case-control study starts with outcome cases and disease-free controls and compares past exposure prevalence; it yields odds ratios. When the outcome is rare, the case-control design is more efficient. When multiple outcomes are of interest or when the outcome is not rare, the retrospective cohort is preferred.

A retrospective cohort is preferable when the outcome has a long latency (decades), when waiting for events to accumulate is impractical, or when the research question must be answered quickly and suitable historical records already exist. A prospective cohort is preferable when exposure measurement must be precise and standardized, when relevant confounders are not in existing records, or when the research question requires biological samples collected prospectively.

Immortal time bias occurs when person-time during which subjects could not have experienced the outcome — for example, the period between cohort entry and receiving an exposure that defines group membership — is incorrectly assigned to the exposed group. It makes the exposed group look artificially healthier. Avoid it by aligning cohort entry, exposure start, and follow-up start carefully, and by using time-varying exposure coding in survival models rather than fixed baseline exposure classification.

First, characterise the extent and likely mechanism of missingness (missing completely at random, at random, or not at random). If missingness is limited and plausibly random, complete-case analysis with sensitivity analysis is acceptable. For larger proportions of missing data, multiple imputation is preferred, provided the variables needed to predict missingness are available. Worst-case scenario analyses help bound uncertainty. Avoid imputing the exposure variable itself using the outcome, as this can introduce bias.

Like all observational designs, a retrospective cohort study can demonstrate association and temporal precedence of exposure before outcome, but it cannot rule out unmeasured confounding without additional evidence. Causal claims are strengthened by applying the Bradford Hill criteria (strength, consistency, specificity, dose-response, biological plausibility), by conducting negative control analyses, and by triangulating findings with other study designs including randomized trials where available.