A conceptual framework for cautious escalation of anticancer treatment: How to optimize overall benefit and obviate the need for de-escalation trials.

Pourmir, I; Van Halteren, H K; Elaidi, R; Trapani, D; Strasser, Florian; Vreugdenhil, G; Clarke, M (2024). A conceptual framework for cautious escalation of anticancer treatment: How to optimize overall benefit and obviate the need for de-escalation trials. Cancer treatment reviews, 124, p. 102693. Elsevier 10.1016/j.ctrv.2024.102693

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BACKGROUND

The developmental workflow of the currently performed phase 1, 2 and 3 cancer trial stages lacks essential information required for the determination of the optimal efficacy threshold of new anticancer regimens. Due to this there is a serious risk of overdosing and/or treating for an unnecessary long time, leading to excess toxicity and a higher financial burden for society. But often post-approval de-escalation trials for dose-optimization and treatment de-intensification are not performed due to failing resources and time. Therefore, the developmental workflow needs to be restructured toward cautious systemic cancer treatment escalation, in order to guarantee optimal efficacy and sustainability.

METHODS

In this manuscript we discuss opportunities to produce the information needed for cautious escalation, based on models of cancer growth and cancer kill kinetics as well as exploratory biomarkers, for the purpose of designing the optimal phase 3 superiority trial. Subsequently, we compare the sample size needed for a phase 3 superiority trial, followed by a necessary de-escalation trial with the sample size needed for a multi-arm phase 3 trial with intervention arms of differing intensity. All essential items are structured within a Framework for Cautious Escalation (FCE). The discussion uses illustrations from the breast cancer setting, but aims to be applicable for all cancers.

RESULTS

The FCE is a promising model of clinical development in oncology to prevent overtreatment and associated issues, especially with regard to the number of repetitive treatment cycles. It will hopefully increase the relevance and success rate of clinical trials, to deliver improved patient-centric outcomes.

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