Determining Optimal Cutoff Scores and Neuropsychological Tests for the Diagnosis of Mild Cognitive Impairment in Parkinson's Disease (S37.003)

OBJECTIVE: To determine optimal properties of a neuropsychological battery for identifying Parkinson’s disease mild cognitive impairment (PD-MCI). BACKGROUND: MCI occurs in 20-50% of PD patients and represents a risk factor for PD dementia. The Movement Disorder Society (MDS) Task Force diagnostic criteria require comprehensive neuropsychological assessment for a diagnosis of PD-MCI (Level II). However, the optimal methodology for these criteria, including cutoff scores and neuropsychological tests, remains undefined. DESIGN/METHODS: Seventy-six non-demented PD patients underwent comprehensive neuropsychological assessments (19 tests representing 5 cognitive domains). A diagnosis of PD-MCI by MDS Level II criteria using varying cutoff scores for impairment (1, 1.5, 2 and 2.5 SD below normative values) was compared to PD-MCI diagnosis by expert consensus. Classification measures including sensitivity and specificity were determined for each cutoff. The probability of diagnosing PD-MCI based on number and specific tests per domain, at 1.5 and 2 SD cutoffs, was examined using regression models. RESULTS: Sensitivity and specificity of MDS Level II criteria varied across the different SD cutoffs. The best sensitivity (85.4%) and specificity (78.6%) measures were achieved using a 2 SD cutoff. The other cutoffs compromised either specificity (21.4% at 1 SD; 60.7% at 1.5 SD) or sensitivity (58.4% at 2.5 SD). Overall, there was a greater probability of detecting impairment when more tests per domain were utilized. However, exceeding two tests per domain in the attention and executive function domains did not result in increased detection. Regression models revealed that certain attention, executive, memory, and visuospatial function tests and specific test combinations provide better diagnostic classification of PD-MCI. CONCLUSIONS: Use of different cutoff scores, number and types of neuropsychological tests clearly influence the diagnosis of PD-MCI. Our findings, which answer several unresolved questions of the MDS criteria, provide a basis for optimal, efficient neuropsychological batteries that can be used by clinicians and researchers to diagnose PD-MCI. Study Supported by: K23NS060949 (JGG), Parkinson’s Disease Foundation Disclosure: Dr. Holden has nothing to disclose. Dr. Ouyang has nothing to disclose. Dr. Stebbins has received personal compensation for activities with Adamas Pharmaceuticals, Ceregene Inc., CHDI Management, Ingenix Pharmaceuticals, and Neurocrine Biosciences as a consultant. Dr. Bernard has received research support from the Parkinson9s Disease Foundation. Dr. Goetz has received personal compensation for activities with AOP Orphan, Addex Pharma, Advanced Studies of Medicine, Boston Scientific Corp., CHDI Foundation, Health Advances, ICON Clinical Research, Ingenix, and the National Institutes of Health. Dr. Goetz has received personal compensation in an editorial capacity for Oxford University Press, Elsevier Publishers, Wolters Kluwer Health-Lippincott, Wilkins and Williams, Movement Disorder, American Academy of Neurology, and the Unviersity of Pennsylvania. Dr. Goetz has received research support from the National Institutes of Health, the Michael J Fox Foundation, and The Parkinson9s Disease Foundation. Dr. Goldman has received personal compensation for activities with American Academy of Neurology, Movement Disorder Society, Johns Hopkins Dystonia and Spasticity Practicum, and Teva Neuroscience. Dr. Goldman has received research support from NIH/NINDS and the Parkinson9s Disease Foundation.