Abstract
Cost-effectiveness analysis models for Duchenne muscular dystrophy (DMD)-a rare muscular disease-have been developed based on data from a limited patient population, such as clinical trials. Thus, this study aimed to construct a more robust cost-effectiveness analysis model based on real-world evidence. The model was constructed using the Registry of Muscular Dystrophy (Remudy) database, the national registry of muscular diseases in Japan. Parameters for transition probability and drug cost were estimated based on this registry, and a quality-of-life (QOL) survey was conducted on Remudy-listed patients for utility. A Markov model was adopted using motor functions as outcomes. Age-specific transition probabilities were estimated by fitting a Weibull distribution to Remudy data of 730 patients. For each drug that was dosed according to body weight (BW), drug costs were estimated from the BW information in the Remudy data and direct medical costs were based on Japanese practice guidelines. For utility, QOL values for each state were estimated for 346 patients who consented to the survey. Using a novel approach that leverages the registry's comprehensive epidemiological data and patient's access to research, the refined cost-effectiveness analysis model was developed and this may be fundamental to implementing the health technology assessments of DMD.