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Joint Analysis of Longitudinal and Time-to-Event Data

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Principles and Practice of Clinical Trials

Abstract

The longitudinal and time-to-event data are two kinds of common data generated from various clinical trials across different therapeutic areas. Joint modeling is appropriate to estimate unbiased effect of covariates that are measured longitudinally and are related to the event on the time to an event and then could be applied to predict the time to an event. An underlying random effects structure links the survival and longitudinal sub-models and allows for individual-specific predictions. This chapter provided the basic backgrounds of longitudinal and time-to-event data commonly generated from clinical trials and derivations of the joint likelihood function to be maximized when jointly modeling longitudinal and time-to-event data. In addition to these theoretical backgrounds, different applications of joint modeling of longitudinal and time-to-event data across different therapeutic areas and individual dynamic prediction were also extensively discussed.

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Author information

Authors and Affiliations

  1. Clinical Pharmacology & Exploratory Development, Astellas Pharma, Northbrook, IL, USA

    Zheng Lu

  2. Pharmacometrics, Eli Lilly and Company, Zionsville, IN, USA

    Emmanuel Chigutsa

  3. Clinical Pharmacology, Biogen, Boston, MA, USA

    Xiao Tong

Authors
  1. Zheng Lu
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  2. Emmanuel Chigutsa
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  3. Xiao Tong
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Editor information

Editors and Affiliations

  1. Samuel Oschin Comprehensive Cancer Insti, WEST HOLLYWOOD, CA, USA

    Steven Piantadosi

  2. Bloomberg School of Public Health, Johns Hopkins Center for Clinical Trials Bloomberg School of Public Health, Baltimore, MD, USA

    Curtis L. Meinert

Section Editor information

  1. Department of Biostatistics and Bioinformatics, Basic Science Division, Duke University School of Medicine, Durham, NC, USA

    Stephen L. George PhD

  2. The Johns Hopkins Center for Clinical Trials and Evidence Synthesis, Johns Hopkins School of Public Health, Baltimore, MA, USA

    Curtis L. Meinert

  3. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Steven Piantadosi

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Lu, Z., Chigutsa, E., Tong, X. (2021). Joint Analysis of Longitudinal and Time-to-Event Data. In: Piantadosi, S., Meinert, C.L. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52677-5_131-1

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  • DOI: https://doi.org/10.1007/978-3-319-52677-5_131-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52677-5

  • Online ISBN: 978-3-319-52677-5

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

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