Abstract

Cancer biomarker discoveries typically involve using patient specimens. In practice, there is often strong desire to preserve high quality biospecimens for studies that are most likely to yield useful information. Previously, we proposed a two-stage adaptive design for binary endpoints which terminates the biomarker study in a futility interim if the model performance is unsatisfactory. In this work, we extend the two-stage design framework to accommodate time-to-event endpoints. The first stage of the procedure involves testing whether the measure of discrimination for survival models (C-index) exceeds a prespecified threshold. We describe the computation of cross-validated C-index and evaluation of the statistical significance using resampling techniques. The second stage involves an independent model validation. Our simulation studies show that under the null hypothesis, the proposed design maintains Type I error at the nominal level and has high probabilities of terminating the study early. Under the alternative hypothesis, power of the design is a function of the true event proportion, the sample size, and the targeted improvement in the discriminant measure. We apply the method to design of a prognostic biomarker study in patients with triple-negative breast cancer. Some practical aspects of the proposed method are discussed.

摘要

癌症生物标志物的发现通常涉及使用患者标本。在实践中，人们常常强烈希望为最有可能产生有用信息的研究保存高质量的生物样本。以前，我们提出了一种二元终点的两阶段自适应设计，如果模型性能不令人满意，该设计将在无效的过渡期终止生物标志物研究。在这项工作中，我们扩展了两阶段设计框架以适应事件发生时间端点。该程序的第一阶段涉及测试生存模型（C指数）的歧视措施是否超过预先指定的阈值。我们描述了交叉验证C的计算-使用重采样技术对统计显着性进行索引和评估。第二阶段涉及独立模型验证。我们的模拟研究表明，在零假设下，所提出的设计将 I 类错误保持在标称水平，并且很可能提前终止研究。在备择假设下，设计的功效是真实事件比例、样本大小和判别测量的目标改进的函数。我们将该方法应用于三阴性乳腺癌患者预后生物标志物研究的设计。讨论了所提出方法的一些实际方面。