Hierarchical Bayesian modelling of disease progression to inform clinical trial design in centronuclear myopathy.

ABSTRACT:

Background

Centronuclear myopathies are severe rare congenital diseases. The clinical variability and genetic heterogeneity of these myopathies result in major challenges in clinical trial design. Alternative strategies to large placebo-controlled trials that have been used in other rare diseases (e.g., the use of surrogate markers or of historical controls) have limitations that Bayesian statistics may address. Here we present a Bayesian model that uses each patient's own natural history study data to predict progression in the absence of treatment. This prospective multicentre natural history evaluated 4-year follow-up data from 59 patients carrying mutations in the MTM1 or DNM2 genes.

Methods

Our approach focused on evaluation of forced expiratory volume in 1 s (FEV1) in

SUBMITTER: Fouarge E 

PROVIDER: S-EPMC7789189 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature