A bayesian nonlinear mixed-effects disease progression model

HIGHLIGHTS

• who: Seongho Kim from the Biostatistics Core, Karmanos Cancer Institute, Department of Oncology, Wayne State University School of Medicine, Detroit, MI, USA have published the article: A Bayesian Nonlinear Mixed-Effects Disease Progression Model, in the Journal: (JOURNAL)
• what: The aims of this study were to resolve the two aforementioned issues: (i) finding a proper sensitivity model and_(ii) estimating the disease progression models by considering variation in age. The authors propose a generalized sensitivity model which depends on age at diagnosis, time spent in the preclinical state and sojourn time, and the developed sensitivity . . .
  

   

  

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