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Toward Evidence Synthesis of Adverse Events in Imbalanced Time-to-Event Data
Zhen Peng1,2, Jingyi Jiang3, Lifeng Lin4
1Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
Journal of Evidence-Based Medicine
|July 1, 2026
Summary
Imbalanced exposure time in studies significantly biases adverse event estimations. Ignoring exposure duration, especially with >20% imbalance, is inappropriate; consider individual participant data for accurate harm effect synthesis.
Area of Science:
- Biostatistics
- Epidemiology
- Clinical Research Methodology
Background:
- Standard evidence synthesis for adverse events often overlooks imbalanced exposure durations between study arms.
- This oversight can lead to inaccurate pooled effect estimates for harm outcomes.
Purpose of the Study:
- To investigate the impact of imbalanced exposure time on the estimation of adverse event effects in evidence synthesis.
- To evaluate methods for addressing exposure time differences in meta-analyses.
Main Methods:
- Simulated individual participant time-to-event data using Cox proportional hazards and Weibull distributions.
- Collapsed data into aggregated form for hierarchical Binomial and Poisson regression models.
- Assessed percentage bias, mean squared error, and coverage probability.
Main Results:
- Imbalanced exposure time (>20% difference) substantially impacts harm effect estimation in meta-analysis.
- Incidence Rate Ratio (IRR) estimation is suitable for non-recurrent events with low to moderate heterogeneity.
- A case study of 22 trials confirmed biased estimations due to imbalanced exposure.
Conclusions:
- Ignoring significant exposure time differences (>20%) in meta-analysis is inappropriate.
- While IRR can be useful, prioritizing the collection of individual participant data is crucial for accurate adverse event synthesis.
- Time-to-event data analysis requires careful consideration of exposure duration.
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