Widmer, Lukas Andreas, Weber, Sebastian, Xu, Yunnan and Weber, Hans-Jochen (2025) Towards Efficient Time-to-Event Dose-Escalation Guidance of Multi-Cycle Cancer Therapies. Statistics in medicine, 44 (20-22). e70229. ISSN 1097-0258; 0277-6715

Abstract

Treatment of cancer has rapidly evolved over time in quite dramatic ways, for example, from chemotherapies, targeted therapies to immunotherapies and chimeric antigen receptor T-cells. Nonetheless, the basic design of early phase I trials in oncology still follows predominantly a dose-escalation design. These trials monitor safety over the first treatment cycle to escalate the dose of the investigated drug. However, over time, studying additional factors such as drug combinations and/or variation in the timing of dosing became important as well. Existing designs were continuously enhanced and expanded to account for increased trial complexity. With toxicities occurring at later stages beyond the first cycle and the need to treat patients over multiple cycles, the focus on the first treatment cycle only is becoming a limitation in nowadays multi-cycle treatment therapies. Here, we introduce a multi-cycle time-to-event model (TITE-CLRM: Time-Interval-To-Event Complementary-Loglog Regression Model), allowing guidance of dose-escalation trials studying multi-cycle therapies. The challenge lies in balancing the need to monitor the safety of longer treatment periods with the need to continuously enroll patients safely. The proposed multi-cycle time-to-event model is formulated as an extension to established concepts like the escalation with overdose control principle. The model is motivated by a current drug development project and evaluated in a simulation study.

Item Type:	Article
Keywords:	Bayesian logistic regression model | dose-finding | estimand | maximum tolerated dose | oncology | overdosecontrol | phase I trial | time-to-event data
Date Deposited:	09 Oct 2025 00:45
Last Modified:	09 Oct 2025 00:45
URI:	https://oak.novartis.com/id/eprint/57774