Quantifying the impact of immortal time bias: empirical evidence from meta-analyses

Objectives: Immortal time bias (ITB) occurs when a period during which, by design, participants cannot experience the outcome (like death) is incorrectly included in the treatment group’s follow-up, artificially making the treatment look better than it truly is. We aimed to identify a systematic sample of cases of ITB in the literature of studies using survival analysis and assess the impact of ITB on the results. Design: Meta-epidemiological study (PROSPERO[CRD42022356073]). Setting: We searched PubMed/MEDLINE, Embase and Cochrane Database of Systematic Reviews from database inception to August 2024. Systematic reviews with quantitative syntheses that allowed subgroup analysis by the presence of ITB for any available exposure-outcome pairs (‘topics’) were eligible for inclusion. Participants: Participants included in the systematic reviews. Main outcome measures: Information on ITB and effect sizes (ESs) with 95% confidence interval for individual studies in forest plots were extracted to run re-analysis using generic inverse variance fixed- and random-effects methods. After extracting data, we conducted subgroup analysis by the presence of ITB for all available topics and assessed the impact of ITB on the heterogeneity (I²), vulnerability of evidence (or conclusion), statistical significance of the finding, and altering ES in favour of intervention/exposure. Results: The median (interquartile range (IQR)) number of studies included for a topic was 6 (4–10). Across 25 topics (including 182 studies), 44.0% of the eligible studies (80 studies) were affected by ITB. Among the 21 topics where both studies with ITB and studies without ITB were available (four topics only had studies unaffected by ITB), 57.1% (12/21) demonstrated statistically significant results only in studies with ITB (n = 11 topics) or only in studies without ITB (one topic). In 23.8% (5/21), the overall summary results changed from statistically significant to non-statistically significant or vice versa after excluding studies with ITB. The ratio of ES – summary ES from studies with ITB relative to summary ES from studies without ITB – was 0.71 (95% CI, 0.66-0.78), suggesting that the ES from studies with ITB was larger by an average of 29% in favour of the intervention/exposure. Excluding studies involving ITB reduced between-study heterogeneity (I²) by 21.4% on average. Conclusions: ITB can be common among studies in some medical areas, and its presence may substantially inflate the ESs and lead to misleading, exaggerated evidence.