Adjusting for Truncated Study Duration in Recurrent Event Analysis - A Weighting Approach for Clinical Trials

Sep 30, 2026

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Recurrent event analysis with fixed follow-up intervals can suffer bias and reduced precision when follow-up is truncated by early dropout or study termination, often underestimating event risks in clinical trials. A time-based weighting approach is proposed using the ratio of observed-to-expected follow-up duration within the Prentice-Williams-Peterson Gap Time model. The method is evaluated via simulations and applied to a double-blinded trial on calcium supplementation for preeclampsia prevention. Results show lower bias and improved precision, with smaller standard errors and a more conservative hazard ratio for hypertension family history.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages9

Reading Time23 min

AccessFree to download

Abstract

Background

Methods

Results

Conclusion

Introduction

Cox model and recurrent events

Informative censoring and bias

Funding and competing interests

Data availability and abbreviations

OPEN ACCESS Citation: Michael Raj A J, Thomas T, Dwarkanath P (2026) Adjusting for truncated study duration in recurrent event analysis: A weighting approach for clinical trials. PLoSOne 21(1): e0339887. [https://doi.org/10.1371/](https://doi.org/10.1371/)[ ](https://doi.org/10.1371/)[journal.pone.0339887](journal.pone.0339887) Editor: Farshid Danesh, Islamic World Science & Technology Monitoring and Citation Institute (ISC), IRAN, ISLAMIC REPUBLIC OF Received: July 11, 2025 Accepted: December 13, 2025 Published: January 7, 2026 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: [https://doi.org/10.1371/journal](https://doi.org/10.1371/journal). pone.0339887 Copyright: © 2026 Michael Raj A et al. This isan open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, RESEARCH ARTICLE Adjusting for truncated study duration in recurrent event analysis: A weighting approach for clinical trials John Michael Raj A1,2, Tinku Thomas2*, Pratibha Dwarkanath3 1 Center for Doctoral Studies, Manipal Academy of Higher Education, Manipal, India, 2 Department of Biostatistics, St. John’s Medical college, Bangalore, India, 3 Division of Nutrition, St. John’s Research Institute, Bangalore, India * tinku.sarah@sjri. res. in Abstract Background 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. Methods We propose a time-based weighting approach using the ratio of observed-toexpected 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 therecurrent event. Results Simulations 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 amore conservative hazard ratio for hypertension family history (weighted HR = 1. 14, SE = 0.054 vs. unweighted HR = 1.23, SE = 0.065) . Conclusion Unaccounted truncated follow-up in recurrent event studies can bias the risk estimation if unaccounted for. Our findings demonstrate that total time-based weighting PLOS One | [https://doi.org/10.1371/journal.pone.0339887](https://doi.org/10.1371/journal.pone.0339887) January 7, 2026 1 / 9 distribution, and reproduction in any medium, provided the original author and source are credited. Data availability statement: The dataset used for demonstration in this manuscript is derived from a third-party randomized controlled trial: Dwarkanath P, Muhihi A, Sudfeld CR, Wylie BJ, Wang M, Perumal N, et al. Two Randomized Trials of Low-Dose Calcium Supplementation in Pregnancy. N Engl J Med. 2024;390(2):143–53 . The authors do not own the rights to share these data; all data-sharing rights remain exclusively with the study Principal Investigator (PI) . As detailed in the original publication’s data-sharing policy, complete de-identified patient-level data from the trial may be made available to qualified researchers. Access is granted only upon formal request to the PI, accompanied by a research proposal and the necessary approvals from the Institutional Ethics Committee (IEC) and other relevant regulatory authorities. The PI details, as

FAQs

Why does truncated follow-up create bias in recurrent event analysis?

Truncation from early dropout or study termination breaks the fixed follow-up structure, which can bias risk estimates and reduce precision, often underestimating event risks.

What weighting approach is proposed in this paper?

The paper proposes time-based weighting using the ratio of observed-to-expected follow-up duration in the Prentice-Williams-Peterson Gap Time (PWP-GT) model.

How was the method evaluated and what were the key findings?

The method was assessed through simulations and then applied to a double-blinded clinical trial. Weighted analysis showed lower bias and improved precision, with smaller standard errors and a more conservative hazard ratio for hypertension family history.

Sep 30, 2026

Uploaded by OmBimo