Categorising trajectories and individual item changes of the North Star Ambulatory Assessment in patients with Duchenne muscular dystrophy

Functional variability among boys with Duchenne muscular dystrophy (DMD) is well recognised and complicates interpretation of clinical studies. We hypothesised that boys with DMD could be clustered into groups sharing similar trajectories of ambulatory function over time, as measured by the North Star Ambulatory Assessment (NSAA) total score. We also explored associations with other variables such as age, functional abilities, and genotype. Using the NorthStar Clinical Network database, 395 patients with >1 NSAA assessment were identified. We utilised latent class trajectory analysis of longitudinal NSAA scores, which produced evidence for at least four clusters of boys sharing similar trajectories versus age in decreasing order of clinical severity: 25% of the boys were in cluster 1 (NSAA falling to <= 5 at age similar to 10y), 35% were in cluster 2 (NSAA <= 5 similar to 12y), 21% in were cluster 3 (NSAA <= 5 similar to 14y), and 19% in cluster 4 (NSAA > 5 up to 15y). Mean ages at diagnosis of DMD were similar across clusters (4.2, 3.9, 4.3, and 4.8y, respectively). However, at the first NSAA assessment, a significant (p<0.05) association was observed between earlier declining clusters and younger age, worse NSAA, slower rise from supine, slower 10 metre walk/run times, and younger age of steroid initiation. In order to assess the probability of observing complete loss of function for individual NSAA items, we examined the proportion of patients who shifted from a score of 1 or 2 at baseline to a score of 0. We also assessed the probability of gain of function using the inverse assessment and stratified the probability of deterioration, improvement-or static behavior-by age ranges and using baseline functional status. Using this tool, our study provides a comprehensive assessment of the NSAA in a large population of patients with DMD and, for the first time, describes discrete clusters of disease progression; this will be invaluable for future DMD clinical trial design and interpretation of findings.