ArticlePloS one2026
Adjusting for truncated study duration in recurrent event analysis: A weighting approach for clinical trials.
Article in PloS one, 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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3 authors.
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Abstract
backgroundIn recurrent event analysis with fixed follow-up intervals, truncated follow-up due to early dropout or study termination introduces bias and reduces precision in risk estimates, particularly in clinical trials where shorter observation periods may underestimate event risks.
methodsWe propose a time-based weighting approach using the ratio of observed-to-expected follow-up duration in the Prentice-Williams-Peterson Gap Time (PWP-GT) model. The method was evaluated in simulations and applied to a double-blinded trial (N = 4000) comparing 500 mg vs. 1500 mg daily calcium supplementation for preeclampsia prevention. For demonstration of the problem and application of the weighting method, drug non-adherence at follow-up visits was considered as the recurrent event.
resultsSimulations showed the weighted PWP-GT model had lower bias (1.0% vs. 1.3%) and improved precision compared to the unweighted model, with coverage probabilities >94%. In the trial data, weighting yielded smaller standard errors and a more conservative hazard ratio for hypertension family history (weighted HR = 1.14, SE = 0.054 vs. unweighted HR = 1.23, SE = 0.065).
conclusionUnaccounted truncated follow-up in recurrent event studies can bias the risk estimation if unaccounted for. Our findings demonstrate that total time-based weighting effectively addresses this bias and enhances precision in both simulated and real datasets.
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