Journal
AMERICAN JOURNAL OF EPIDEMIOLOGY
Volume 174, Issue 3, Pages 354-363Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/aje/kwr081
Keywords
antiparkinsonian agents; Parkinson disease; prediction; predictive value of tests; prescriptions; prevalence
Categories
Funding
- l'Institut National de la Sante et de la Recherche Medicale
- l'Agence Nationale de la Recherche
- l'Agence Francxaise de Securite Sanitaire de l'Environnement et du Travail
- Ministere de l'Enseignement Superieur et de la Recherche
- Fondation pour la Recherche Medicale
- France Parkinson
Ask authors/readers for more resources
Drug claims databases are increasingly available and provide opportunities to investigate epidemiologic questions. The authors used computerized drug claims databases from a social security system in 5 French districts to predict the probability that a person had Parkinson's disease (PD) based on patterns of antiparkinsonian drug (APD) use. Clinical information for a population-based sample of persons using APDs in 2007 was collected. The authors built a prediction model using demographic variables and APDs as predictors and investigated the additional predictive benefit of including information on dose and regularity of use. Among 1,114 APD users, 320 (29%) had PD and 794 (71%) had another diagnosis as determined by study neurologists. A logistic model including information on cumulative APD dose and regularity of use showed good performance (c statistic = 0.953, sensitivity = 92.5%, specificity = 86.4%). Predicted PD prevalence (among persons aged >= 18 years) was 6.66/1,000; correcting this estimate using sensitivity/specificity led to a similar figure (6.04/1,000). These data demonstrate that drug claims databases can be used to estimate the probability that a person is being treated for PD and that information on APD dose and regularity of use improves models' performances. Similar approaches could be developed for other conditions.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available