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Parkinson disease (PD) is the second most common neurodegenerative disorder. Its diagnosis relies solely on a clinical examination and is not straightforward because no diagnostic test exists. Large, population-based, prospective cohort studies designed to examine other outcomes that are more common than PD might provide cost-efficient alternatives for studying the disease. However, most cohort studies have not implemented rigorous systematic screening for PD. A majority of epidemiologic studies that utilize population-based prospective designs rely on secondary data sources to identify PD cases. Direct validation of these secondary sources against clinical diagnostic criteria is lacking. The Framingham Heart Study has prospectively screened and evaluated participants for PD based on clinical diagnostic criteria. We assessed the predictive value of secondary sources for PD identification relative to clinical diagnostic criteria in the Framingham Heart Study (2001-2012). We found positive predictive values of 1.0 (95% confidence interval: 0.868, 1.0), 1.0 (95% confidence interval: 0.839, 1.0), and 0.50 (95% confidence interval: 0.307, 0.694) for PD identified from self-report, use of antiparkinsonian medications, and Medicare claims, respectively. The negative predictive values were all higher than 0.99. Our results highlight the limitations of using only Medicare claims data and suggest that population-based cohorts may be utilized for the study of PD determined via self-report or medication inventories while preserving a high degree of confidence in the validity of PD case identification.

Validation of Secondary Data Sources to Identify Parkinson Disease Against Clinical Diagnostic Criteria