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

Denis Rustand, Laurent Briollais, Virginie Rondeau

Research output: Contribution to journalArticlepeer-review


The 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.
Original languageEnglish (US)
JournalPharmaceutical Statistics
StatePublished - Sep 17 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-09-20
Acknowledgements: Canadian Institutes of Health Research;Canadian Statistical Science Institute; Ecole des Hautes Etudes en SantéPublique - Réseau Doctoral; InstitutNational Du Cancer, Grant/AwardNumber: 2017-0680; Natural Sciences andEngineering Research Council of Canada. This publication is based on research using information obtained from www.projectdatasphere.org, which is maintained by Project Data Sphere, LLC.

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)


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