Two-part joint model for a longitudinal semicontinuous marker and a terminal event with application to metastatic colorectal cancer data

Author:

Rustand Denis1,Briollais Laurent2,Tournigand Christophe3,Rondeau Virginie1

Affiliation:

1. Department of Biostatistics, Bordeaux Population Health Research Center, INSERM U1219, 146 Rue Léo Saignat, 33076 Bordeaux, France

2. 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

3. Hôpital Henri Mondor, 51 Avenue du Maréchal de Lattre de Tassigny, 94010 Créteil, France

Abstract

Summary 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).

Funder

National Cancer Institute

Canadian Institute of Health Research

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

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