Disease Progression Stages and Burden in Patients with Duchenne Muscular Dystrophy Using Administrative Claims Supplemented by Electronic Medical Records.

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.

Rasch Analysis of the Pediatric Quality of Life Inventory 4.0 Generic Core Scales Administered to Patients With Duchenne Muscular Dystrophy.

OBJECTIVES: The objective of this study was to examine the psychometric properties of the Pediatric Quality of Life Inventory 4.0 Generic Core Scales (PedsQL 4.0 GCS) in Duchenne muscular dystrophy (DMD), a rare, severely debilitating, and ultimately fatal neuromuscular disease. METHODS: Patients with DMD were recruited from 20 centers across 9 countries as part of the Cooperative International Neuromuscular Research Group Duchenne Natural History Study (NCT00468832). The psychometric properties of the PedsQL 4.0 GCS were examined using Rasch analysis. RESULTS: In total, 329 patients with DMD (mean age 9 years, range 3-18 years, 75% ambulatory) completed the PedsQL 4.0 GCS. The most difficult instrument items, expressing the greatest loss in health-related quality of life, were those associated with emotional well-being (eg, being teased by other children, feeling sad, and not making friends), as opposed to somatic disability (eg, lifting heavy objects, participating in sports, and running). The mean item and person fit residuals were estimated at 0.301 (SD: 1.385) and -0.255 (1.504), respectively. In total, 87% (20 of 23) of items displayed disordered thresholds, and many exhibited nontrivial dependency. The overall item-trait interaction χ2 value was 178 (115 degrees of freedom, P<.001). Our analysis also revealed significant issues with differential item functioning, and by investigating residual principal component loadings, the PedsQL 4.0 GCS total score was found to be multidimensional. CONCLUSIONS: The PedsQL 4.0 GCS records information clinically relevant to patients with DMD, but the total scale score may not be fit for purpose as a measure health-related quality of life in this disease population.