A Joint Model Considering Measurement Errors for Optimally Identifying Tumor Mutation Burden Threshold.
A Joint Model Considering Measurement Errors for Optimally Identifying Tumor Mutation Burden Threshold.
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DOI：
10.3389/fgene.2022.915839
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发表时间：
2022
影响因子：
3.7
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中科院分区：
文献类型：
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肿瘤突变负荷（Tumor mutation burden， TMB）是公认的免疫治疗分层生物标志物。然而，由于临床存在严重的争议，普遍的TMB高阈值不规范，其根本原因是多种评估标准不一致，TMB值不精确。现有的确定TMB阈值的方法都只考虑临床获益的单一维度，而忽略了TMB误差的干扰。我们的研究旨在基于考虑测量误差的多方面临床疗效来确定最佳的TMB阈值。我们报告了一个多端点联合模型作为推断TMB阈值的广义方法，使用考虑错误指定协变量的迭代数值估计过程促进一致的统计推断。该模型通过结合客观反应率和时间到事件结果来优化划分，这两个结果可能由于一些共同的特征而相互关联。我们通过启用特定主题的随机效应来控制不同端点之间的通信，从而增强了以前的工作。仿真结果表明，该模型在参数估计和阈值确定的精度和稳定性方面优于标准模型。为了验证所提出阈值的可行性，我们汇集了73例接受抗pd -(L)1治疗的非小细胞肺癌患者和64例鼻咽癌患者的队列，以及943例患者的验证队列。分析表明，我们的方法可以给予临床医生一个全面的疗效评估，最终确定优质患者的TMB筛查阈值。我们的方法有潜力在治疗选择和支持精确免疫肿瘤学方面产生创新的见解。
Tumor mutation burden (TMB) is a recognized stratification biomarker for immunotherapy. Nevertheless, the general TMB-high threshold is unstandardized due to severe clinical controversies, with the underlying cause being inconsistency between multiple assessment criteria and imprecision of the TMB value. The existing methods for determining TMB thresholds all consider only a single dimension of clinical benefit and ignore the interference of the TMB error. Our research aims to determine the TMB threshold optimally based on multifaceted clinical efficacies accounting for measurement errors. We report a multi-endpoint joint model as a generalized method for inferring the TMB thresholds, facilitating consistent statistical inference using an iterative numerical estimation procedure considering mis-specified covariates. The model optimizes the division by combining objective response rate and time-to-event outcomes, which may be interrelated due to some shared traits. We augment previous works by enabling subject-specific random effects to govern the communication among distinct endpoints. Our simulations show that the proposed model has advantages over the standard model in terms of precision and stability in parameter estimation and threshold determination. To validate the feasibility of the proposed thresholds, we pool a cohort of 73 patients with non-small-cell lung cancer and 64 patients with nasopharyngeal carcinoma who underwent anti-PD-(L)1 treatment, as well as validation cohorts of 943 patients. Analyses revealed that our approach could grant clinicians a holistic efficacy assessment, culminating in a robust determination of the TMB screening threshold for superior patients. Our methodology has the potential to yield innovative insights into therapeutic selection and support precision immuno-oncology.