Interim Monitoring as an Information-Time Alignment Problem: The WCR Framework for Time-to-Event Trials

2026-06-13

AI Summary

This study addresses the longstanding challenge in time-to-event trials of balancing inferential maturity with practical feasibility during interim monitoring, where conventional event-driven or enrollment-driven approaches suffer from inherent limitations. The authors propose the WCR framework, which reframes interim monitoring as an information–time alignment problem. By fixing the cohort size and calibrating follow-up requirements, WCR enables continued enrollment while synchronizing interim analyses with information maturity, reserving later-enrolled patients for the final analysis. The framework explicitly distinguishes follow-up constraints between landmark survival estimators and proportional hazards models, jointly calibrates design parameters and decision thresholds, and integrates constrained optimization, simulation-based calibration, and Bayesian methods, implemented in the open-source R package WCRBayesDesign. In simulations of rare pediatric oncology trials, WCR substantially improves the stability and interpretability of interim analysis timing while rigorously controlling Type I error and maintaining power, outperforming existing strategies.

Abstract

Interim monitoring in time-to-event trials must balance inferential maturity with operationally meaningful timing. Event-driven designs align analyses with event accumulation but can produce substantial and unpredictable calendar delays, whereas enrollment-driven designs provide predictable timing but may rely on immature follow-up. We propose the Window-Cohort with Calibrated Follow-Up Requirement (WCR) framework, which directly parameterizes follow-up maturity through a locked cohort size and a post-lock follow-up requirement. The interim analysis is conducted after the prespecified cohort has accrued the calibrated minimum follow-up, while enrollment may continue and later patients are reserved for the final analysis. The framework distinguishes restricted follow-up for landmark survival estimands from unrestricted follow-up for proportional hazards estimands, thereby linking the effective information horizon to the estimand. Design parameters and decision thresholds are jointly calibrated through constrained optimization to control type I error and power while balancing calendar time, interim maturity, and decision-lag burden. Simulation studies motivated by a rare pediatric oncology trial show that WCR attains target operating characteristics under the calibration model and offers more stable and interpretable interim timing than conventional event-driven and enrollment-driven approaches. The methodology is implemented in the open-source R package WCRBayesDesign, available on CRAN. WCR reframes interim monitoring as an information-time alignment problem and provides a practical design strategy for single-arm trials with sparse events, slow accrual, and long-horizon endpoints.

Problem

• interim monitoring
• time-to-event trials
• follow-up maturity
• information-time alignment
• trial design

Innovation

• interim monitoring
• time-to-event trials
• follow-up maturity
• information-time alignment
• WCR framework