文章：

优化单阶段与两阶段肿瘤学试验中比例的单样本检验方法

Optimizing One-Sample Tests for Proportions in Single- and Two-Stage Oncology Trials

原文发布日期：4 August 2025

DOI: 10.3390/cancers17152570

类型: Article

开放获取: 是

英文摘要：

Background/Objectives: Phase II oncology trials often rely on single-arm designs to testH0:π=π0versusHa:π>π0, especially when randomized trials are infeasible due to cost or disease rarity. Traditional approaches, such as the exact binomial test and Simon’s two-stage design, tend to be conservative, with actual Type I error rates falling below the nominalαdue to the discreteness of the underlying binomial distribution. This study aims to develop a more efficient and flexible method that maintains accurate Type I error control in such settings. Methods: We propose a convolution-based method that combines the binomial distribution with a simulated normal variable to construct an unbiased estimator ofπ. This method is designed to precisely control the Type I error rate while enabling more efficient trial designs. We derive its theoretical properties and assess its performance against traditional exact tests in both one-stage and two-stage trial designs. Results: The proposed method results in more efficient designs with reduced sample sizes compared to standard approaches, without compromising the control of Type I error rates. We introduce a new two-stage design incorporating interim futility analysis and compare it with Simon’s design. Simulations and real-world examples demonstrate that the proposed approach can significantly lower trial cost and duration. Conclusions: This convolution-based approach offers a flexible and efficient alternative to traditional methods for early-phase oncology trial design. It addresses the conservativeness of existing designs and provides practical benefits in terms of resource use and study timelines.

摘要翻译： 

背景/目的：在肿瘤学II期临床试验中，由于成本或疾病罕见性等因素导致随机试验难以实施时，常采用单臂设计来检验H0:π=π0与Ha:π>π0。传统方法如精确二项检验和西蒙两阶段设计，由于基础二项分布的离散性，其实际I类错误率往往低于名义α水平，趋于保守。本研究旨在开发一种更高效、灵活的方法，在此类情境下保持对I类错误率的精确控制。方法：我们提出一种基于卷积的方法，将二项分布与模拟正态变量相结合，构建π的无偏估计量。该方法旨在精确控制I类错误率的同时，实现更高效的试验设计。我们推导了其理论性质，并在单阶段和两阶段试验设计中评估其相对于传统精确检验的性能。结果：与传统方法相比，所提方法在保证I类错误率控制的前提下，实现了样本量更少的高效设计。我们引入了一种包含期中无效性分析的新型两阶段设计，并与西蒙设计进行比较。模拟研究和实际案例表明，该方法能显著降低试验成本与周期。结论：这种基于卷积的方法为早期肿瘤学试验设计提供了一种灵活高效的传统方法替代方案。它解决了现有设计的保守性问题，并在资源利用和研究周期方面具有实际优势。

原文链接：

Optimizing One-Sample Tests for Proportions in Single- and Two-Stage Oncology Trials