Muscular Dystrophy Surveillance, Tracking, and Research Network pilot: Population‐based surveillance of major muscular dystrophies at four U.S. sites, 2007–2011

• Published in: Birth defects research 2018-11, Vol.110 (19), p.1404-1411
• Main Authors: Do, ThuyQuynh N., Street, Natalie, Donnelly, Jennifer, Adams, Melissa M., Cunniff, Christopher, Fox, Deborah J., Weinert, Richard O., Oleszek, Joyce, Romitti, Paul A., Westfield, Christina P., Bolen, Julie
• Format: Article
• Language: English
• Subjects: active surveillance; Adolescent; Adult; Arizona - epidemiology; Child; Clinical Modification (ICD‐9‐CM) codes; Colorado - epidemiology; Databases, Factual; Epidemiological Monitoring; Female; Humans; International Classification of Diseases; Iowa - epidemiology; Male; MD STARnet; medical record abstraction; Middle Aged; muscular dystrophies; Muscular Dystrophies - classification; Muscular Dystrophies - diagnosis; Muscular Dystrophies - epidemiology; Muscular Dystrophy, Duchenne - diagnosis; Muscular Dystrophy, Duchenne - epidemiology; New York - epidemiology; Ninth Revision; Population Surveillance - methods; population‐based; Prevalence; Public Health; Registries; Retrospective Studies; United States
• ISSN: 2472-1727; 2472-1727
• DOI: 10.1002/bdr2.1371

Background For 10 years, the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) conducted surveillance for Duchenne and Becker muscular dystrophy (DBMD). We piloted expanding surveillance to other MDs that vary in severity, onset, and sources of care. Methods Our retrospective surveillance included individuals diagnosed with one of nine eligible MDs before or during the study period (January 2007–December 2011), one or more health encounters, and residence in one of four U.S. sites (Arizona, Colorado, Iowa, or western New York) at any time within the study period. We developed case definitions, surveillance protocols, and software applications for medical record ion, clinical review, and data pooling. Potential cases were identified by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM) codes 359.0, 359.1, and 359.21 and International Classification of Diseases, Tenth Revision (ICD‐10) codes G71.0 and G71.1. Descriptive statistics were compared by MD type. Percentage of MD cases identified by each ICD‐9‐CM code was calculated. Results Of 2,862 cases, 32.9% were myotonic, dystrophy 25.8% DBMD, 9.7% facioscapulohumeral MD, and 9.1% limb‐girdle MD. Most cases were male (63.6%), non‐Hispanic (59.8%), and White (80.2%). About, half of cases were genetically diagnosed in self (39.1%) or family (6.2%). About, half had a family history of MD (48.9%). The hereditary progressive MD code (359.1) was the most common code for identifying eligible cases. The myotonic code (359.21) identified 83.4% of eligible myotonic dystrophy cases (786/943). Conclusions MD STARnet is the only multisite, population‐based active surveillance system available for MD in the United States. Continuing our expanded surveillance will contribute important epidemiologic and health outcome information about several MDs.