Joel Iff1, Yi Zhong2, Deepshekhar Gupta3, Xander Paul3, Edward Tuttle3, Erik Henricson4, Rachel Schrader5. 1. Sarepta Therapeutics, Inc, Cambridge, MA, USA. 2. Analysis Group, Inc., 1010 El Camino Real #310, Menlo Park, CA, 94025, USA. Yi.Zhong@analysisgroup.com. 3. Analysis Group, Inc., 1010 El Camino Real #310, Menlo Park, CA, 94025, USA. 4. UC Davis Medical Center, Sacramento, CA, USA. 5. Parent Project Muscular Dystrophy, Hackensack, NJ, USA.
Abstract
INTRODUCTION: This study aims to identify stages of Duchenne muscular dystrophy (DMD) and assess the disease burden by progression stage using real-world administrative claims supplemented by relevant electronic medical record (EMR) data. METHODS: Claims and EMR data from the Decision Resources Group's Real World Data Repository (2011-2020) were used to identify patients with DMD by diagnosis code and to stratify them into four disease stages by diagnosis and procedure markers reflective of DMD progression. Clinical and medical history data from the Cooperative International Neuromuscular Research Group (CINRG) were used to validate the developed claims-based staging algorithm. The distribution and drivers by disease stage, as well as disease burden, were examined. RESULTS: A total of 938 (94%) of patients with DMD identified in claims/EMR data had sufficient information for stage classification. Patients were classified by stage based on patient characteristics and the presence or absence of progression markers such as genetic testing, wheelchair usage, scoliosis treatment, or ventilation assistance. Average ages at stages 1-4 are 7, 13, 18, and 23 years, respectively. Using natural history data, the claims-based staging algorithm was validated with high sensitivity and specificity rates. Both healthcare resource utilization and medical charges increased by stage. For example, the average annualized total charges were $17,688 (stage 1), $36,868 (stage 2), $72,801 (stage 3), and $167,285 (stage 4). CONCLUSIONS: Large-scale claims data supplemented by EMR data can be used to characterize DMD progression and evaluate disease burden which may inform the design of future real-world studies about DMD.
INTRODUCTION: This study aims to identify stages of Duchenne muscular dystrophy (DMD) and assess the disease burden by progression stage using real-world administrative claims supplemented by relevant electronic medical record (EMR) data. METHODS: Claims and EMR data from the Decision Resources Group's Real World Data Repository (2011-2020) were used to identify patients with DMD by diagnosis code and to stratify them into four disease stages by diagnosis and procedure markers reflective of DMD progression. Clinical and medical history data from the Cooperative International Neuromuscular Research Group (CINRG) were used to validate the developed claims-based staging algorithm. The distribution and drivers by disease stage, as well as disease burden, were examined. RESULTS: A total of 938 (94%) of patients with DMD identified in claims/EMR data had sufficient information for stage classification. Patients were classified by stage based on patient characteristics and the presence or absence of progression markers such as genetic testing, wheelchair usage, scoliosis treatment, or ventilation assistance. Average ages at stages 1-4 are 7, 13, 18, and 23 years, respectively. Using natural history data, the claims-based staging algorithm was validated with high sensitivity and specificity rates. Both healthcare resource utilization and medical charges increased by stage. For example, the average annualized total charges were $17,688 (stage 1), $36,868 (stage 2), $72,801 (stage 3), and $167,285 (stage 4). CONCLUSIONS: Large-scale claims data supplemented by EMR data can be used to characterize DMD progression and evaluate disease burden which may inform the design of future real-world studies about DMD.