ArticleJournal of evidence-based medicine2026
Toward Evidence Synthesis of Adverse Events in Imbalanced Time-to-Event Data.
Article in Journal of evidence-based medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
backgroundThe routine approach in evidence synthesis of adverse events is to estimate the odds ratio or risk ratio of each individual study and then synthesize the study-specific effects for a pooled average estimate, while seldom consider the potential imbalanced duration of exposures of study arms. This article aims to investigate the potential impact of imbalanced exposure time on harm effects.
methodsWe simulated individual participant time-to-event data based on Cox proportional hazard model, with Weibull function to reshape the distribution of the hazards. We further collapsed the data into aggregated one and fitting both hierarchical Binomial regression model and hierarchical Poisson regression model to estimate the pooled RR and incidence rate ratio (IRR). The percentage bias, mean squared error, and coverage probability were examined.
resultsOur results suggested that imbalanced exposure time between study arms can have substantial impact on the estimation of harm effects in evidence synthesis, especially when the extent of the imbalance exceeds 20%. Estimating an IRR to address the imbalanced exposure time only made sense for non-recurrent events when the between-study heterogeneity is small or moderate. A case study by 22 ongoing trials verified the potential biased estimation when exposure time was imbalanced between study arms.
conclusionsIt is inappropriate to ignoring exposure time when there is a large difference (> 20%) between study arms; while the IRR could be used in some cases, collecting individual participant data for evidence synthesis of adverse events for time-to-event data should be the primary consideration.
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