BACKGROUND AND OBJECTIVES: Clinical trials of genotype-targeted treatments in Duchenne muscular dystrophy (DMD) traditionally compare treated patients to untreated patients with the same DMD genotype class. This avoids confounding of drug efficacy by genotype effects but also shrinks the pool of eligible controls, increasing challenges for trial enrollment in this already rare disease. To evaluate the suitability of genotypically unmatched controls in DMD, we quantified effects of genotype class on 1-year changes in motor function endpoints used in clinical trials. METHODS: Over 1,600 patient-years of follow-up (>700 patients) were studied from six real-world/natural history data sources (UZ Leuven, PRO-DMD-01 shared by CureDuchenne, iMDEX, North Star UK, Cincinnati Children's Hospital Medical Center, and the DMD Italian Group), with genotypes classified as amenable to skipping exons 44, 45, 51 or 53, other skippable, nonsense, and other mutations. Associations between genotype class and 1-year changes in North Star Ambulatory Assessment total score (ΔNSAA) and in 10-meter walk/run velocity (Δ10MWR) were studied in each data source with and without adjustment for baseline prognostic factors. RESULTS: The studied genotype classes accounted for approximately 2% of variation in ΔNSAA outcomes after 12 months, whereas other prognostic factors explained >30% of variation in large data sources. Based on a meta-analysis across all data sources, pooled effect estimates for the studied skip-amenable mutation classes were all small in magnitude (<2 units in ΔNSAA total score in 1-year follow up), smaller than clinically important differences in NSAA, and were precisely estimated with standard errors <1 unit after adjusting for non-genotypic prognostic factors. DISCUSSION: These findings suggest viability of trial designs incorporating genotypically mixed or unmatched controls for up to 12 months in duration for motor function outcomes, which would ease recruitment challenges and reduce numbers of patients assigned to placebos. Such trial designs, including multi-genotype platform trials and hybrid designs, should ensure baseline balance between treatment and control groups for the most important prognostic factors, while accounting for small remaining genotype effects quantified in the present study
