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- Title
Use of Artificial Networks in Clinical Trials: A Pilot Study to Predict Responsiveness to Donepezil in Alzheimer's Disease.
- Authors
Mecocci, Patrizia; Grossi, Enzo; Buscema, Massimo; Intraligi, Marco; Savarè, Rita; Rinaldi, Patrizia; Cherubini, Antonio; Senin, Umberto
- Abstract
OBJECTIVES: To evaluate the accuracy of artificial neural networks compared with discriminant analysis in classifying positive and negative response to the cholinesterase inhibitor donepezil in a group of Alzheimer's disease (AD) patients. DESIGN: Convenience sample. SETTING: Patients with mild to moderate AD consecutively admitted to a geriatric day hospital and treated with donepezil 5 mg/day. PARTICIPANTS: Sixty-one older patients of both sexes with AD. MEASUREMENTS: Accuracy in detecting subjects sensitive (responders) or not (nonresponders) to 3-month therapy with ANNs. The criterion standard for evaluation of efficacy was the scores of Alzheimer's Disease Assessment Scale—Cognitive portion and Clinician's Interview Based Impression of Change—plus scales. RESULTS: ANNs were more effective in discriminating between responders and nonresponders than other advanced statistical methods, particularly linear discriminant analysis. The total accuracy in predicting the outcome was 92.59%. CONCLUSIONS: ANNs appear to be a useful tool in detecting patient responsiveness to pharmacological treatment in AD.
- Subjects
BIOLOGICAL neural networks; ALZHEIMER'S disease
- Publication
Journal of the American Geriatrics Society, 2002, Vol 50, Issue 11, p1857
- ISSN
0002-8614
- Publication type
Article
- DOI
10.1046/j.1532-5415.2002.50516.x