Adjusting for truncated study duration in recurrent event analysis: A weighting approach for clinical trials
John Michael Raj A, Tinku Thomas, Pratibha Dwarkanath, Farshid Danesh, Farshid Danesh, Farshid Danesh
TL;DR
This paper introduces a weighting method to reduce bias in risk estimates caused by early dropout or study termination in clinical trials with recurrent events.
Contribution
A novel time-based weighting approach is proposed to adjust for truncated follow-up in recurrent event analysis.
Findings
The weighted PWP-GT model showed lower bias (1.0% vs. 1.3%) and improved precision in simulations.
Weighting reduced standard errors and produced more conservative hazard ratios in real trial data.
Abstract
In 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. We 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. Simulations showed the weighted PWP-GT model had lower bias (1.0% vs. 1.3%) and improved precision compared to the unweighted…
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Taxonomy
TopicsPregnancy and preeclampsia studies · Advanced Causal Inference Techniques · Genetic Associations and Epidemiology