Disease progression modeling of the North Star Ambulatory Assessment (NSAA) for Duchenne Muscular Dystrophy (DMD).
Jennifer E HibmaPriya JayachandranSrividya NeelakantanLutz O HarnischPublished in: CPT: pharmacometrics & systems pharmacology (2023)
Duchenne Muscular Dystrophy (DMD) is a rare genetic disorder caused by decreased or absent dystrophin gene leading to progressive muscle degeneration and weakness in young boys. Disease progression models for the North Star Ambulatory Assessment (NSAA), a functional measurement widely used to assess outcomes in clinical trials, were developed using a longitudinal population modeling approach. The relationship between NSAA total score over time, loss of ambulation, and potential covariates that may influence disease progression were evaluated. Data included individual participant observations from an internal placebo-controlled Phase 2 clinical trial and from the external natural history database for males with DMD obtained through the Cooperative International Neuromuscular Research Group (CINRG). A modified indirect response model for NSAA joined to a loss-of ambulation (LOA) time-to-event model described the data well. Age was used as the independent variable since ambulatory function is known to vary with age. The NSAA and LOA models were linked using the dissipation rate constant parameter (k out ) from the NSAA model by including the parameter as a covariate on the hazard equation for LOA. No covariates were identified. The model was then used as a simulation tool to explore various clinical trial design scenarios. This model contributes to the quantitative understanding of disease progression in DMD and may guide model-informed drug development decisions for ongoing and future DMD clinical trials.
Keyphrases
- duchenne muscular dystrophy
- clinical trial
- muscular dystrophy
- blood pressure
- phase ii
- study protocol
- randomized controlled trial
- open label
- skeletal muscle
- type diabetes
- genome wide
- radiation therapy
- machine learning
- high resolution
- climate change
- big data
- phase iii
- weight loss
- placebo controlled
- insulin resistance
- locally advanced
- human health