Department of Biostatistics, Bordeaux Population Health Research Center, INSERM U1219, 146 Rue Léo Saignat, 33076 Bordeaux, France.
Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital and Dalla Lana School of Public Health (Biostatistics), University of Toronto, 600 University Ave., Ontario M5G 1X5, Canada.
Biostatistics. 2022 Jan 13;23(1):50-68. doi: 10.1093/biostatistics/kxaa012.
Joint models for a longitudinal biomarker and a terminal event have gained interests for evaluating cancer clinical trials because the tumor evolution reflects directly the state of the disease. A biomarker characterizing the tumor size evolution over time can be highly informative for assessing treatment options and could be taken into account in addition to the survival time. The biomarker often has a semicontinuous distribution, i.e., it is zero inflated and right skewed. An appropriate model is needed for the longitudinal biomarker as well as an association structure with the survival outcome. In this article, we propose a joint model for a longitudinal semicontinuous biomarker and a survival time. The semicontinuous nature of the longitudinal biomarker is specified by a two-part model, which splits its distribution into a binary outcome (first part) represented by the positive versus zero values and a continuous outcome (second part) with the positive values only. Survival times are modeled with a proportional hazards model for which we propose three association structures with the biomarker. Our simulation studies show some bias can arise in the parameter estimates when the semicontinuous nature of the biomarker is ignored, assuming the true model is a two-part model. An application to advanced metastatic colorectal cancer data from the GERCOR study is performed where our two-part model is compared to one-part joint models. Our results show that treatment arm B (FOLFOX6/FOLFIRI) is associated to higher SLD values over time and its positive association with the terminal event leads to an increased risk of death compared to treatment arm A (FOLFIRI/FOLFOX6).
联合模型用于纵向生物标志物和终末事件,已引起癌症临床试验评估的关注,因为肿瘤的演变直接反映了疾病的状态。随时间推移描述肿瘤大小演变的生物标志物对于评估治疗方案非常有用,并且可以与生存时间一起考虑。生物标志物通常具有半连续分布,即,它是零膨胀和右偏的。需要为纵向生物标志物以及与生存结果的关联结构建立适当的模型。在本文中,我们提出了一种用于纵向半连续生物标志物和生存时间的联合模型。纵向生物标志物的半连续性质由两部分模型指定,该模型将其分布分为二进制结果(第一部分),由阳性与零值表示,以及仅具有阳性值的连续结果(第二部分)。生存时间采用比例风险模型进行建模,我们提出了三种与生物标志物关联的结构。我们的模拟研究表明,当忽略生物标志物的半连续性质时,参数估计可能会出现偏差,假设真实模型是两部分模型。对 GERCOR 研究中晚期转移性结直肠癌数据进行了应用,将我们的两部分模型与单部分联合模型进行了比较。我们的结果表明,与治疗臂 A(FOLFIRI/FOLFOX6)相比,治疗臂 B(FOLFOX6/FOLFIRI)随时间推移与更高的 SLD 值相关,并且与终末事件的正相关导致死亡风险增加。