A Multi-Arm Two-Stage (MATS) design for proof-of-concept and dose optimization in early-phase oncology trials

医学 阶段(地层学) 最大耐受剂量 肿瘤科 概念证明 临床试验 内科学 医学物理学 计算机科学 古生物学 生物 操作系统
作者
Zhenghao Jiang,Gu Mi,Lin Ji,Christelle Lorenzato,Yuan Ji
出处
期刊:Contemporary Clinical Trials [Elsevier BV]
卷期号:132: 107278-107278 被引量:12
标识
DOI:10.1016/j.cct.2023.107278
摘要

The Project Optimus initiative by the FDA's Oncology Center of Excellence is widely viewed as a groundbreaking effort to change the status quo of conventional dose-finding strategies in oncology. Unlike in other therapeutic areas where multiple doses are evaluated thoroughly in dose ranging studies, early-phase oncology dose-finding studies are characterized by the practice of identifying a single dose, such as the maximum tolerated dose (MTD) or the recommended phase 2 dose (RP2D). Following the spirit of Project Optimus, we propose an Multi-Arm Two-Stage (MATS) design for proof-of-concept (PoC) and dose optimization that allows the evaluation of two selected doses from a dose-escalation trial. The design assesses the higher dose first across multiple indications in the first stage, and adaptively enters the second stage for an indication if the higher dose exhibits promising anti-tumor activities. In the second stage, a randomized comparison between the higher and lower doses is conducted to achieve PoC and dose optimization. A Bayesian hierarchical model governs the statistical inference and decision making by borrowing information across doses, indications, and stages. Our simulation studies show that the proposed MATS design yield desirable performance. An R Shiny application has been developed and made available at https://matsdesign.shinyapps.io/mats/.
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