Development and validation of a Bayesian survival model for inclusion body myositis.

ABSTRACT:

Background

Associations between disease characteristics and payer-relevant outcomes can be difficult to establish for rare and progressive chronic diseases with sparse available data. We developed an exploratory bridging model to predict premature mortality from disease characteristics, and using inclusion body myositis (IBM) as a representative case study.

Methods

Candidate variables that may be potentially associated with premature mortality were identified by disease experts and from the IBM literature. Interdependency between candidate variables in IBM patients were assessed using existing patient-level data. A Bayesian survival model for the IBM population was developed with identified variables as predictors for premature mortality in the model. For model selection and

SUBMITTER: Capkun G 

PROVIDER: S-EPMC6836518 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature