Zhang Baoshan, Sun Jong-Mu, Ahn Myung-Ju, Jung Sin-Ho
Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27705, USA.
Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul 135-710, Republic of Korea.
Biomedicines. 2024 Sep 26;12(10):2185. doi: 10.3390/biomedicines12102185.
The design of cancer clinical trials incorporating biomarkers depends on various factors, including the trial phase, the type of biomarker and whether its role has been validated. This article aims to present a method for designing and analyzing phase II cancer clinical trials that validate predictive biomarkers.
We propose a randomized trial design where patients are allocated between a targeted therapy and a non-targeted therapy stratified by biomarker status. Tumor response is used as the primary endpoint to validate the biomarker through interaction testing between treatment and biomarker positivity. Additionally we propose a sample size calculation method for this design, considering two types of interaction: one based on logit-transformed response rates and the other on raw response rates.
The proposed sample size method is applied to the design of a real randomized phase II trial. Extensive simulations are conducted to evaluate the performance of the test statistic and the sample size method under different scenarios.
Our method provides a practical approach to validating predictive biomarkers in phase II cancer trials. The simulations demonstrate robust performance for both interaction models, offering guidance for the sample size selection and analysis strategy in biomarker-stratified trials.
纳入生物标志物的癌症临床试验设计取决于多种因素，包括试验阶段、生物标志物类型及其作用是否已得到验证。本文旨在介绍一种设计和分析验证预测性生物标志物的II期癌症临床试验的方法。
我们提出一种随机试验设计，根据生物标志物状态将患者分配至靶向治疗组和非靶向治疗组。通过治疗与生物标志物阳性之间的交互作用检验，将肿瘤反应用作验证生物标志物的主要终点。此外，我们针对该设计提出一种样本量计算方法，考虑两种交互作用类型：一种基于对数转换后的缓解率，另一种基于原始缓解率。
所提出的样本量方法应用于一项真实的随机II期试验设计。进行了广泛的模拟，以评估不同场景下检验统计量和样本量方法的性能。
我们的方法为在II期癌症试验中验证预测性生物标志物提供了一种实用方法。模拟显示两种交互作用模型均具有稳健性能，为生物标志物分层试验中的样本量选择和分析策略提供了指导。
