A dose-finding approach for genomic patterns in phase I trials.
A dose-finding approach for genomic patterns in phase I trials.
复制标题
I 期试验中基因组模式的剂量探索方法。
DOI：
10.1080/10543406.2020.1744619
复制
发表时间：
2020
影响因子：
1.1
通讯作者：
Hamada C.
中科院分区：
文献类型：
--
作者：
Kaneko S;Hirakawa A;Kakurai Y;Hamada C.
精准医学是一种新兴的疾病治疗和预防方法，它考虑了基因、环境和生活方式的个体差异。癌症是一种基因组疾病;因此，基于基因组突变模式，癌症中分子靶向药物的剂量-功效和剂量-毒性关系很可能不同。个体化最佳剂量-具有临床可接受安全性特征的最大有效剂量-可能会因基因组突变模式而异，应在精密医学中使用这些药物之前确定。此外，影响个体化最佳剂量的基因应在早期发育阶段确定。在这项研究中，我们提出了一种新的剂量发现方法，以确定个性化的最佳剂量的分子靶向药物在I期癌症试验。基于L1和L2惩罚回归，同时进行个体化最佳剂量确定和基因选择。与大多数报告的剂量探索方法相似，本研究考虑了剂量-疗效和剂量-毒性关系的非单调模式，以及基于多项分布的疗效和毒性结局之间的相关性。我们的剂量发现算法是基于估计的惩罚回归模型计算的预测概率。我们比较了不同情况下的模拟研究所提出的和现有的方法之间的操作特性。
Precision medicine is an emerging approach for disease treatment and prevention that accounts for individual variability in genes, environment, and lifestyle. Cancer is a genomic disease; therefore, the dose-efficacy and dose–toxicity relationships for molecularly targeted agents in cancer most likely differ, based on the genomic mutation pattern. The individualized optimal dose – the maximal efficacious dose with a clinically acceptable safety profile – may vary depending on the genomic mutation patterns and should be determined prior to the use of these agents in precision medicine. In addition, genes that influence the individualized optimal doses should be identified in early-phase development. In this study, we propose a novel dose-finding approach to identify the individualized optimal dose for molecularly targeted agents in phase I cancer trials. Individualized optimal dose determination and gene selection were conducted simultaneously based onL1andL2penalized regression. Similar to most reported dose-finding approaches, this study considers non-monotonic patterns for dose-efficacy and dose–toxicity relationships, as well as correlations between efficacy and toxicity outcomes based on multinomial distribution. Our dose-finding algorithm is based on the predictive probability calculated with an estimated penalized regression model. We compare the operating characteristics between the proposed and existing methods by simulation studies under various scenarios.