AIM: The aim of this study was to determine whether use of antiparkinsonian drugs in pharmacy records can be used as a marker for patients with Parkinson's disease (PD). METHOD: Data were obtained from the Rotterdam Study, a community-based prospective cohort study among people aged 55 years or older who were all screened for PD. For 5510 persons, of whom 74 had PD, pharmacy records were available. Stepwise logistic regression analysis was used to evaluate whether age, sex and use of the antiparkinsonian drugs amantadine, anticholinergics, dopamine agonists, levodopa and selegiline, were predictive variables for PD. For each individual a probability for having PD was calculated. Sensitivity, specificity and positive predictive value (PPV) were calculated at different cut-off values based on calculated probabilities. RESULTS: More than 90% of the users of levodopa, bromocriptine, selegiline, and users of at least two different antiparkinsonian drugs had PD. Age, use of amantadine, anticholinergics, bromocriptine, levodopa, and selegiline were predictive variables for PD. After application of different cut-off values, sensitivity was at most 66.2%, and specificity was at least 99.8%. A PPV of higher than 90% was obtained at higher probabilities. CONCLUSION: Based on the high PPV of our predictive model, antiparkinsonian drugs can be used as a reliable marker for PD in pharmacy records. Because sensitivity is low, pharmacy records cannot be used to estimate prevalence of PD.
AIM: The aim of this study was to determine whether use of antiparkinsonian drugs in pharmacy records can be used as a marker for patients with Parkinson's disease (PD). METHOD: Data were obtained from the Rotterdam Study, a community-based prospective cohort study among people aged 55 years or older who were all screened for PD. For 5510 persons, of whom 74 had PD, pharmacy records were available. Stepwise logistic regression analysis was used to evaluate whether age, sex and use of the antiparkinsonian drugs amantadine, anticholinergics, dopamine agonists, levodopa and selegiline, were predictive variables for PD. For each individual a probability for having PD was calculated. Sensitivity, specificity and positive predictive value (PPV) were calculated at different cut-off values based on calculated probabilities. RESULTS: More than 90% of the users of levodopa, bromocriptine, selegiline, and users of at least two different antiparkinsonian drugs had PD. Age, use of amantadine, anticholinergics, bromocriptine, levodopa, and selegiline were predictive variables for PD. After application of different cut-off values, sensitivity was at most 66.2%, and specificity was at least 99.8%. A PPV of higher than 90% was obtained at higher probabilities. CONCLUSION: Based on the high PPV of our predictive model, antiparkinsonian drugs can be used as a reliable marker for PD in pharmacy records. Because sensitivity is low, pharmacy records cannot be used to estimate prevalence of PD.
Authors: Maurits E L Arbouw; Kris L L Movig; Cees Neef; Henk-Jan Guchelaar; Toine C G Egberts Journal: Eur J Clin Pharmacol Date: 2007-01-03 Impact factor: 2.953
Authors: M E L Arbouw; K L L Movig; T P van Staa; A C G Egberts; P C Souverein; F de Vries Journal: Osteoporos Int Date: 2010-10-22 Impact factor: 4.507
Authors: Maurits E L Arbouw; Kris L L Movig; Henk-Jan Guchelaar; Cees Neef; Toine C G Egberts Journal: Eur J Clin Pharmacol Date: 2011-07-22 Impact factor: 2.953