Developing a Natural History Model for Duchenne Muscular Dystrophy

Abstract

Abstract Background The aim of this study was to build a natural history model (NHM) for Duchenne muscular dystrophy (DMD) to provide new insights into the disease and to inform economic evaluations of new therapies. The study was conducted as part of Project HERCULES, a multi-stakeholder collaboration to develop tools to support the health technology assessment of new treatments for DMD. Methods Health states were identified based on a review of NHMs and input from clinicians, patients, and caregivers, and defined using outcomes commonly collected in clinical trials and real-world practice. The primary data source informing the NHM was the Critical Path Institute Duchenne Regulatory Science Consortium (D-RSC) database. This was supplemented, where data were scarce or absent, with expert input obtained via an elicitation exercise, and a systematic literature review and meta-analysis of mortality data. Results The NHM includes ambulatory, transfer, and non-ambulatory phases. Health states capture progression in each phase including loss of ambulation, ability to weight bear, and upper body and respiratory function, respectively. Scoliosis and cardiomyopathy were not included in health state definitions as the reporting of data in D-RSC for these diagnoses was poor. The NHM estimates that patients spend approximately 9.5 years in ambulatory states, 1.5 years in the transfer state, and the remainder of their lives in non-ambulatory states, with a median predicted survival of 29.8 years (95% CI: 29.1, 30.8). Conclusion The model developed includes a detailed disease pathway for DMD, including the clinically, patient, caregiver, and economically important transfer state which has not been identified or included in previous NHMs. The NHM will aid the understanding of disease milestones and may be used to support economic evaluations for new treatments for DMD, help facilitate inclusion of a lifetime time horizon within economic models and identify areas for further research.