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Activity Number: 362
Type: Topic Contributed
Date/Time: Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305733
Title: Computational Intelligence-Based Data Mining for the Minimal Clinically Relevant Difference in the Unified Parkinson's Disease Rating Scale
Author(s): Nitzan Mekel-Bobrov*+
Companies: Boston Scientific Corporation
Address: 25155 Rye Canyon Loop, Valencia, CA, 91355,
Keywords: Mining ; Parkinson's ; UPDRS ; MCRD ; MCID
Abstract:

The Unified Parkinson's Disease Rating Scale (UPDRS) is currently the gold standard in rating the symptoms of patients with Parkinson's disease (PD) for clinical, research, and regulatory purposes. A major difficulty, however, is the lack of a robust definition for a minimal clinically relevant difference (MCRD) in UPDRS scores. Quantification of this parameter would offer many advantages in designing and analyzing clinical trials. This paper presents a data mining method, based on a computational intelligence framework, for estimating the MCRD of a health outcome score. Using previously published clinical trial data, this method is then applied to the Unified Parkinson's Disease Rating Scale to establish a clinically significant change in PD patient response to medical intervention.


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