Use of imaging biomarkers and ambulatory functional endpoints in Duchenne muscular dystrophy clinical trials: Systematic review and machine learning-driven trend analysis.

Abstract

Duchenne muscular dystrophy (DMD) is a rare X-linked genetic muscle disorder affecting primarily pediatric males and leading to limited life expectancy. This systematic review of 85 DMD trials and non-interventional studies (2010-2022) evaluated how magnetic resonance imaging biomarkers-particularly fat fraction and T2 relaxation time-are currently being used to quantitatively track disease progression and how their use compares to traditional mobility-based functional endpoints. Imaging biomarker studies lasted on average 4.50 years, approximately 11 months longer than those using only ambulatory functional endpoints. While 93% of biologic intervention trials (n = 28) included ambulatory functional endpoints, only 13.3% (n = 4) incorporated imaging biomarkers. Small molecule trials and natural history studies were the predominant contributors to imaging biomarker use, each comprising 30.4% of such studies. Small molecule trials used imaging biomarkers more frequently than biologic trials, likely because biologics often target dystrophin, an established surrogate biomarker, while small molecules lack regulatory-approved biomarkers. Notably, following the 2018 FDA guidance finalization, we observed a significant decrease in new trials using imaging biomarkers despite earlier regulatory encouragement. This analysis demonstrates that while imaging biomarkers are increasingly used in natural history studies, their integration into interventional trials remains limited. From XGBoost machine learning analysis, trial duration and start year were the strongest predictors of biomarker usage, with a decline observed following the 2018 FDA guidance. Despite their potential to objectively track disease progression, imaging biomarkers have not yet been widely adopted as primary endpoints in therapeutic trials, likely due to regulatory and logistical challenges. Future research should examine whether standardizing imaging protocols or integrating hybrid endpoint models could bridge the regulatory gap currently limiting biomarker adoption in therapeutic trials.