Bayesian model of disease progression in GNE myopathy.

Abstract:

:One Sentence Summary: A Bayesian repeated measures model based on quantitative muscle strength data from a prospective Natural History Study was developed to determine disease progression and design clinical trials for GNE myopathy, a rare and slowly progressive muscle disease. GNE myopathy is a rare muscle disease characterized by slowly progressive weakness and atrophy of skeletal muscles. To address the significant challenges of defining the natural history and designing clinical trials for GNE myopathy, we developed a Bayesian latent variable repeated measures model to determine disease progression. The model is based on longitudinal quantitative muscle strength data collected as part of a prospective Natural History Study. The GNE Myopathy Progression Model provides an understanding of disease progression that would have otherwise required a natural history of unfeasible duration. "Disease age," the model-generated measure of disease progression, highly correlates with a variety of clinical, functional and patient-reported outcomes. With the incorporation of a treatment effect parameter to the GNE Disease Progression Model, we describe a novel GNE Myopathy Disease Modification Analysis that significantly increases power and reduces the number of subjects required to test the effectiveness of novel therapies when compared to more traditional analysis methods. The GNE Myopathy Disease Progression Model and Disease Modification Analysis can be applied to muscle diseases with prospectively collected muscle strength data, and a variety of rare and slowly progressive diseases.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Quintana M,Shrader J,Slota C,Joe G,McKew JC,Fitzgerald M,Gahl WA,Berry S,Carrillo N

doi

10.1002/sim.8050

subject

Has Abstract

pub_date

2019-04-15 00:00:00

pages

1459-1474

issue

8

eissn

0277-6715

issn

1097-0258

journal_volume

38

pub_type

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