A marginalized two‐part joint model for a longitudinal biomarker and a terminal event with application to advanced head and neck cancers

Author:

Rustand Denis12ORCID,Briollais Laurent3,Rondeau Virginie1

Affiliation:

1. UMR1219, Inserm Bordeaux Population Health Center, University of Bordeaux Bordeaux France

2. Statistics Program, Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

3. Lunenfeld‐Tanenbaum Research Institute, Mount Sinai Hospital and Dalla Lana School of Public Health (Biostatistics) University of Toronto Toronto Ontario Canada

Abstract

AbstractThe sum of the longest diameter (SLD) of the target lesions is a longitudinal biomarker used to assess tumor response in cancer clinical trials, which can inform about early treatment effect. This biomarker is semicontinuous, often characterized by an excess of zeros and right skewness. Conditional two‐part joint models were introduced to account for the excess of zeros in the longitudinal biomarker distribution and link it to a time‐to‐event outcome. A limitation of the conditional two‐part model is that it only provides an effect of covariates, such as treatment, on the conditional mean of positive biomarker values, and not an overall effect on the biomarker, which is often of clinical relevance. As an alternative, we propose in this article, a marginalized two‐part joint model (M‐TPJM) for the repeated measurements of the SLD and a terminal event, where the covariates affect the overall mean of the biomarker. Our simulation studies assessed the good performance of the marginalized model in terms of estimation and coverage rates. Our application of the M‐TPJM to a randomized clinical trial of advanced head and neck cancer shows that the combination of panitumumab in addition with chemotherapy increases the odds of observing a disappearance of all target lesions compared to chemotherapy alone, leading to a possible indirect effect of the combined treatment on time to death.

Funder

Canadian Institutes of Health Research

Institut National Du Cancer

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Pharmacology (medical),Pharmacology,Statistics and Probability

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