Utility of capture-recapture methodology to assess completeness of amyotrophic lateral sclerosis case ascertainment

Background: With the establishment of a national amyotrophic lateral sclerosis (ALS) registry in the United States, methods are needed to ascertain the completeness of case ascertainment, especially in view of the proposal to rely largely on existing data sources. Methods: Data about ALS patients residing in the 5-county metropolitan Atlanta area (within the State of Georgia) from 2001 to 2005 were categorized according to their source-ALS Association, clinical (Emory Healthcare, community neurologist, Veterans Health Administration, Veterans Benefits Administration), Medicare and death certificates. ALS diagnoses were verified using chart review. Capture-recapture analyses were carried out using log-linear modeling, stratified by age and race. Results: The final model (based on 798 cases), which included the 4 main sources and 3 two-way interaction terms, yielded an estimated total population of 880 (95% CI 816-965), indicating that the combination of case-finding methods identified about 90.7% of cases. The estimated 5-year period prevalence is 38.5/100,000 (95% CI 35.66-42.19). Conclusion: This study highlights gaps in data based on existing data sources and illustrates a method for combining data from multiple sources to help facilitate the successful establishment of a US national ALS registry.