Latent variable indirect response joint modeling of a continuous and a categorical clinical endpoint

  • Chuanpu HuEmail author
  • Philippe O. Szapary
  • Alan M. Mendelsohn
  • Honghui Zhou
Original Paper


Informative exposure–response modeling of clinical endpoints is important in drug development. There has been much recent progress in latent variable modeling of ordered categorical endpoints, including the application of indirect response (IDR) models and accounting for residual correlations between multiple categorical endpoints. This manuscript describes a framework of latent-variable-based IDR models that facilitate easy simultaneous modeling of a continuous and a categorical clinical endpoint. The model was applied to data from two phase III clinical trials of subcutaneously administered ustekinumab for the treatment of psoriatic arthritis, where Psoriasis Area and Severity Index scores and 20, 50, and 70 % improvement in the American College of Rheumatology response criteria were used as efficacy endpoints. Visual predictive check and external validation showed reasonable parameter estimation precision and model performance.


Discrete variable Multivariate analysis Population pharmacokinetic/pharmacodynamic modeling NONMEM Ustekinumab Psoriatic arthritis Well-controlled clinical trials 



The authors thank the Medical Affairs Publication Group of Janssen Scientific Affairs, LLC for their excellent editorial support.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Chuanpu Hu
    • 1
    Email author
  • Philippe O. Szapary
    • 2
  • Alan M. Mendelsohn
    • 2
  • Honghui Zhou
    • 1
  1. 1.Pharmacokinetics and PharmacometricsBiologics Clinical Pharmacology, Janssen Research and Development, LLCSpring HouseUSA
  2. 2.Clinical ImmunologyJanssen Research and Development, LLCSpring HouseUSA

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