Literature DB >> 32282877

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

Denis Rustand1, Laurent Briollais2, Christophe Tournigand3, Virginie Rondeau1.   

Abstract

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).
© The Author 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Cancer (solid tumors); Joint model; Semicontinuous data; Two-part model; Zero inflation

Mesh:

Substances:

Year:  2022        PMID: 32282877      PMCID: PMC9116390          DOI: 10.1093/biostatistics/kxaa012

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.279


  3 in total

1.  Joint two-part Tobit models for longitudinal and time-to-event data.

Authors:  Getachew A Dagne
Journal:  Stat Med       Date:  2017-08-10       Impact factor: 2.373

2.  Multivariate joint frailty model for the analysis of nonlinear tumor kinetics and dynamic predictions of death.

Authors:  Agnieszka Król; Christophe Tournigand; Stefan Michiels; Virginie Rondeau
Journal:  Stat Med       Date:  2018-03-26       Impact factor: 2.373

3.  Joint model for left-censored longitudinal data, recurrent events and terminal event: Predictive abilities of tumor burden for cancer evolution with application to the FFCD 2000-05 trial.

Authors:  Agnieszka Król; Loïc Ferrer; Jean-Pierre Pignon; Cécile Proust-Lima; Michel Ducreux; Olivier Bouché; Stefan Michiels; Virginie Rondeau
Journal:  Biometrics       Date:  2016-02-17       Impact factor: 2.571

  3 in total

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