ArticleJournal of neuromuscular diseases2018
Diagnostic Accuracy of Phenotype Classification in Duchenne and Becker Muscular Dystrophy Using Medical Record Data1.
Article in Journal of neuromuscular diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 16 citations in OpenAlex.
- Prophylactic Use of Cardiac Medications and Survival in Duchenne Muscular Dystrophy.Muscle & nerve · 2025Article
- Draft Guidance for Industry Duchenne Muscular Dystrophy, Becker Muscular Dystrophy, and Related Dystrophinopathies - Developing Potential Treatments for the Entire Spectrum of Disease.Journal of neuromuscular diseases · 2024Article
- Evaluation of effects of continued corticosteroid treatment on cardiac and pulmonary function in non-ambulatory males with Duchenne muscular dystrophy from MD STARnet.Muscle & nerve · 2022Article
- Selected clinical and demographic factors and all-cause mortality among individuals with Duchenne muscular dystrophy in the Muscular Dystrophy Surveillance, Tracking, and Research Network.Neuromuscular disorders : NMD · 2022Article
- A population-based study of scoliosis among males diagnosed with a dystrophinopathy identified by the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet).Muscle & nerve · 2022Observational
- Clinical and genetic characteristics of Chinese Duchenne/Becker muscular dystrophy patients with small mutations.Frontiers in neuroscience · 2022Article
- Study of Clinical Features and Diagnosis Pattern of Duchene Muscular Dystrophy in Southern India.Journal of neurosciences in rural practice · 2022Article
- Differentiation of Pediatric-Onset Duchenne and Becker Muscular Dystrophy Subphenotypes Using Data from the Muscular Dystrophy Surveillance Tracking and Research Network (MD STARnet).Journal of neuromuscular diseases · 2022Article
- Health Profile of Preterm Males With Duchenne Muscular Dystrophy.Journal of child neurology · 2021Article
- Health-Related Quality of Life and Emotional Distress Among Mothers of Sons With Muscular Dystrophy as Compared to Sex- and Age Group-Matched Controls.Journal of child neurology · 2021Article
- A child with duchenne muscular dystrophy: A case report of a rare diagnosis among Africans.Clinical case reports · 2020Article
- Longitudinal Study of Three microRNAs in Duchenne Muscular Dystrophy and Becker Muscular Dystrophy.Frontiers in neurology · 2020Article
- The position of nonsense mutations can predict the phenotype severity: A survey on the DMD gene.PloS one · 2020Article
Corrections and comments
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Authors and funding
11 authors at 7 institutions in 1 country.
Funding
Abstract
Dystrophinopathies are caused by mutations in DMD resulting in progressive muscle weakness. They are historically divided into the more severe Duchenne (DMD) and milder Becker (BMD) muscular dystrophy phenotypes. Classification is important for research and clinical care. The purpose of this study was to describe a multi-variable approach to classifying cases from the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) and to assess the accuracy of the diagnostic classification scheme. We used age at loss of mobility, molecular testing results, and age at symptom onset to classify cases as having DMD or BMD and to assess sensitivity and specificity. Mobility status showed low sensitivity and high specificity for predicting DMD (65.5% and 99.3%, respectively) and BMD (62.8% and 97.7%, respectively) phenotypes. Molecular testing showed 90.9% sensitivity and 66.4% specificity for DMD; 76.3% sensitivity and 90.0% specificity for BMD. Age of onset predicted DMD with sensitivity of 73.9% and specificity of 69.0%; BMD had 99.7% specificity and 36.7% sensitivity. Mobility status, molecular test results, and age at symptom onset are important but inconsistent measures for accurately classifying individuals into DMD or BMD phenotypes. These results have implications for prognosis in newly diagnosed individuals and for classifying phenotype in clinical trials.
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