ArticleOrphanet journal of rare diseases2017
Capture-recapture methodology to study rare conditions using surveillance data for fragile X syndrome and muscular dystrophy.
Article in Orphanet journal of rare diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Large-scale observational study of AI-based patient and surgical material verification system in ophthalmology: real-world evaluation in 37 529 cases.BMJ quality & safety · 2025Observational
- Article
- Muscular Dystrophy Surveillance, Tracking, and Research Network pilot: Population-based surveillance of major muscular dystrophies at four U.S. sites, 2007-2011.Birth defects research · 2018Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundRare conditions can be catastrophic for families and the implications for public health can be substantial. Our study compared basic surveillance through active medical record review with a linked administrative data file to assess the number of cases of two rare conditions, fragile X syndrome (FXS) and muscular dystrophy (MD) in a population.
methodsTwo methods of data collection were used to collect information from five counties comprising two standard metropolitan statistical areas of South Carolina. The passive system relied mostly on health claims data using ICD-9 CM diagnostic codes. The active system relied on a nurse abstracting records from a list of all licensed physicians with specialties in neurology, orthopedics, and genetics.
resultsThere were 141 FXS cases and 348 MD cases that met the case definitions using active surveillance. Additional cases were found for both conditions but they were determined to not be true cases. After linking the actively collected MD and FXS cases to passive datasets, we found that the estimated total numbers of cases were similar to using capture-recapture analysis; the positive predictive values for cases identified in the passive system were 56.6% for MD and 75.7% for FXS.
conclusionsApplying capture-recapture methods to passively collected surveillance data for rare health conditions produced an estimate of the number of true cases that was similar to that obtained through active data collection.
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