Prediction model of Parkinson's disease based on antiparkinsonian drug claims.

Frédéric Moisan 1, * Véronique Gourlet 1 Jean-Louis Mazurie 2 Jean-Luc Dupupet 3 Jean Houssinot 3 Marcel Goldberg 4, 5 Ellen Imbernon 5 Christophe Tzourio 1 Alexis Elbaz 1, 5
* Auteur correspondant
1 Neuroépidémiologie
2 Caisse départementale de la Gironde
3 Caisse centrale
4 CESP - Centre de recherche en épidémiologie et santé des populations
5 DST-InVS - Département santé travail
Abstract : 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.
Keywords : antiparkinsonian agents Parkinson disease prediction predictive value of tests prescriptions prevalence
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Article dans une revue
American Journal of Epidemiology, Oxford University Press (OUP), 2011, 174 (3), pp.354-63. 〈10.1093/aje/kwr081〉
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Frédéric Moisan, Véronique Gourlet, Jean-Louis Mazurie, Jean-Luc Dupupet, Jean Houssinot, et al.. Prediction model of Parkinson's disease based on antiparkinsonian drug claims.. American Journal of Epidemiology, Oxford University Press (OUP), 2011, 174 (3), pp.354-63. 〈10.1093/aje/kwr081〉. 〈inserm-00598500〉

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