Hobbs Brian P, Thall Peter F, Lin Steven H
Department of Biostatistics, University of Texas M.D. Anderson Cancer Center, Houston, TX.
Department of Radiation Oncology, University of Texas M.D. Anderson Cancer Center, Houston, TX.
J R Stat Soc Ser C Appl Stat. 2016 Feb;65(2):273-297. doi: 10.1111/rssc.12117. Epub 2015 Oct 26.
Delivering radiation to eradicate a solid tumor while minimizing damage to nearby critical organs remains a challenge. For esophageal cancer, radiation therapy may damage the heart or lungs, and several qualitatively different, possibly recurrent toxicities associated with chemoradiation or surgery may occur, each at two or more possible grades. In this article, we describe a Bayesian group sequential clinical trial design, based on total toxicity burden (TTB) and progression-free survival duration, for comparing two radiation therapy modalities for esophageal cancer. Each patient's toxicities are modeled as a multivariate doubly stochastic Poisson point process, with marks identifying toxicity grades. Each grade of each type of toxicity is assigned a severity weight, elicited from clinical oncologists familiar with the disease and treatments. TTB is defined as a severity-weighted sum over the different toxicities that may occur up to 12 months from the start of treatment. Latent frailties are used to formulate a multivariate model for all outcomes. Group sequential decision rules are based on posterior mean TTB and progression-free survival time. The proposed design is shown to provide both larger power and smaller mean sample size when compared to a conventional bivariate group sequential design.
在将辐射用于根除实体瘤的同时,尽量减少对附近关键器官的损害仍然是一项挑战。对于食管癌,放射治疗可能会损害心脏或肺部,并且可能会出现几种性质不同、可能反复出现的与放化疗或手术相关的毒性反应,每种毒性反应都有两个或更多可能的等级。在本文中,我们描述了一种基于总毒性负担(TTB)和无进展生存期的贝叶斯组序贯临床试验设计,用于比较两种食管癌放射治疗方式。将每位患者的毒性反应建模为一个多变量双随机泊松点过程,用标记来识别毒性等级。从熟悉该疾病和治疗方法的临床肿瘤学家那里获取每种毒性反应类型的每个等级的严重程度权重。TTB被定义为从治疗开始起长达12个月内可能出现的不同毒性反应的严重程度加权总和。使用潜在脆弱性来构建所有结局的多变量模型。组序贯决策规则基于后验均值TTB和无进展生存时间。与传统的双变量组序贯设计相比,所提出的设计显示出具有更大的功效和更小的平均样本量。