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使用纵向替代指标的标志性中介生存分析。

Landmark mediation survival analysis using longitudinal surrogate.

作者信息

Zhou Jie, Jiang Xun, Xia H Amy, Hobbs Brian P, Wei Peng

机构信息

Department of Biostatistics and Pharmacometrics, Neuroscience Global Drug Development, Novartis, East Hanover, NJ, United States.

Center for Design and Analysis, Amgen, Thousand Oaks, CA, United States.

出版信息

Front Oncol. 2023 Jan 17;12:999324. doi: 10.3389/fonc.2022.999324. eCollection 2022.

DOI:10.3389/fonc.2022.999324
PMID:36733365
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9887328/
Abstract

Clinical cancer trials are designed to collect radiographic measurements of each patient's baseline and residual tumor burden at regular intervals over the course of study. For solid tumors, the extent of reduction in tumor size following treatment is used as a measure of a drug's antitumor activity. Statistical estimation of treatment efficacy routinely reduce the longitudinal assessment of tumor burden to a binary outcome describing the presence versus absence of an objective tumor response as defined by RECIST criteria. The objective response rate (ORR) is the predominate method for evaluating an experimental therapy in a single-arm trial. Additionally, ORR is routinely compared against a control therapy in phase III randomized controlled trials. The longitudinal assessments of tumor burden are seldom integrated into a formal statistical model, nor integrated into mediation analysis to characterize the relationships among treatment, residual tumor burden, and survival. This article presents a frameworkfor landmark mediation survival analyses devised to incorporate longitudinal assessment of tumor burden. effect-size measures are developed to quantify the survival treatment mediation effects using longitudinal predictors. Analyses are demonstrated with applications to two colorectal cancer trials. Survival prediction is compared in the presence versus absence of longitudinal analysis. Simulation studies elucidate settings wherein patterns of tumor burden dynamics require longitudinal analysis.

摘要

临床癌症试验旨在在研究过程中定期收集每位患者基线和残余肿瘤负荷的影像学测量数据。对于实体瘤,治疗后肿瘤大小的缩小程度被用作衡量药物抗肿瘤活性的指标。治疗疗效的统计估计通常将肿瘤负荷的纵向评估简化为一个二元结果,即根据RECIST标准描述是否存在客观肿瘤反应。客观缓解率(ORR)是在单臂试验中评估实验性疗法的主要方法。此外,在III期随机对照试验中,ORR通常会与对照疗法进行比较。肿瘤负荷的纵向评估很少被纳入正式的统计模型,也很少被纳入中介分析以描述治疗、残余肿瘤负荷和生存之间的关系。本文提出了一个用于标志性中介生存分析的框架,旨在纳入肿瘤负荷的纵向评估。开发了效应量测量方法,以使用纵向预测因子量化生存治疗中介效应。通过应用于两项结直肠癌试验进行了分析。比较了存在纵向分析和不存在纵向分析时的生存预测。模拟研究阐明了肿瘤负荷动态模式需要纵向分析的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/24594dcb46bf/fonc-12-999324-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/5aaa45f9ae68/fonc-12-999324-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/603ddab53106/fonc-12-999324-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/ba5cce143669/fonc-12-999324-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/24594dcb46bf/fonc-12-999324-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/5aaa45f9ae68/fonc-12-999324-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/603ddab53106/fonc-12-999324-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/ba5cce143669/fonc-12-999324-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9f/9887328/24594dcb46bf/fonc-12-999324-g004.jpg

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