We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard biomarkers are both measured on a set of patient samples, or adopting replicated measures of the error-contaminated standard biomarkers in the original study. This approach is easier to conduct and much less expensive than studies that require new samples from patients randomized to the intervention. In addition, it makes it possible to perform the estimation of the clinical performance quickly, since there will be no requirement to wait for events to occur as would be the case with prospective validation. The treatment selection is assessed via a working model, but the proposed estimator of the mean restricted lifetime is valid even if the working model is misspecified. The proposed approach is assessed through simulation studies and applied to a cancer study.

中文翻译：

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从可重复性研究中评估用于治疗选择的生物标志物。

我们考虑根据之前涉及标准生物标志物的临床试验评估新的或更准确测量的预测性生物标志物以进行治疗选择。我们提出了一种更有效的方法，而不是使用新的生物标志物重新进行临床试验，该方法只需要进行可重复性研究，其中新的生物标志物和标准生物标志物都在一组患者样本上进行测量，或者采用重复的误差测量- 原始研究中被污染的标准生物标志物。与需要随机接受干预的患者的新样本的研究相比，这种方法更容易进行且成本更低。此外，它可以快速进行临床性能的估计，因为不需要像预期验证那样等待事件发生。处理选择是通过工作模型评估的，但即使工作模型指定错误，所提出的平均受限寿命估计量也是有效的。所提出的方法通过模拟研究进行评估并应用于癌症研究。