Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting.
BACKGROUND:Given the high prevalence of cognitive impairment in Parkinson's disease (PD), cognitive screening is important in clinical practice. The Montreal Cognitive Assessment (MoCA) is a frequently used screening test in PD to detect mild cognitive impairment (PD-MCI) and Parkinson's d...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2016-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4954721?pdf=render |
id |
doaj-1ead38def0d44ab0acc45f5efb94464f |
---|---|
record_format |
Article |
spelling |
doaj-1ead38def0d44ab0acc45f5efb94464f2020-11-25T01:45:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01117e015931810.1371/journal.pone.0159318Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting.Sophie FenglerJosef KesslerLars TimmermannAlexandra ZapfSaskia ElbenLars WojteckiOliver TuchaElke KalbeBACKGROUND:Given the high prevalence of cognitive impairment in Parkinson's disease (PD), cognitive screening is important in clinical practice. The Montreal Cognitive Assessment (MoCA) is a frequently used screening test in PD to detect mild cognitive impairment (PD-MCI) and Parkinson's disease dementia (PD-D). However, the proportion in which the subtests are represented in the MoCA total score does not seem reasonable. We present the development and preliminary evaluation of an empirically based alternative scoring system of the MoCA which aims at increasing the overall diagnostic accuracy. METHODS:In study 1, the MoCA was administered to 40 patients with PD without cognitive impairment (PD-N), PD-MCI, or PD-D, as defined by a comprehensive neuropsychological test battery. The new MoCA scoring algorithm was developed by defining Areas under the Curve (AUC) for MoCA subtests in a Receiver Operating Characteristic (ROC) and by weighting the subtests according to their sensitivities and specificities. In study 2, an independent sample of 24 PD patients (PD-N, PD-MCI, or PD-D) was tested with the MoCA. In both studies, diagnostic accuracy of the original and the new scoring procedure was calculated. RESULTS:Diagnostic accuracy increased with the new MoCA scoring algorithm. In study 1, the sensitivity to detect cognitive impairment increased from 62.5% to 92%, while specificity decreased only slightly from 77.7% to 73%; in study 2, sensitivity increased from 68.8% to 81.3%, while specificity stayed stable at 75%. CONCLUSION:This pilot study demonstrates that the sensitivity of the MoCA can be enhanced substantially by an empirically based weighting procedure and that the proposed scoring algorithm may serve the MoCA's actual purpose as a screening tool in the detection of cognitive dysfunction in PD patients better than the original scoring of the MoCA. Further research with larger sample sizes is necessary to establish efficacy of the alternate scoring system.http://europepmc.org/articles/PMC4954721?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sophie Fengler Josef Kessler Lars Timmermann Alexandra Zapf Saskia Elben Lars Wojtecki Oliver Tucha Elke Kalbe |
spellingShingle |
Sophie Fengler Josef Kessler Lars Timmermann Alexandra Zapf Saskia Elben Lars Wojtecki Oliver Tucha Elke Kalbe Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting. PLoS ONE |
author_facet |
Sophie Fengler Josef Kessler Lars Timmermann Alexandra Zapf Saskia Elben Lars Wojtecki Oliver Tucha Elke Kalbe |
author_sort |
Sophie Fengler |
title |
Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting. |
title_short |
Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting. |
title_full |
Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting. |
title_fullStr |
Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting. |
title_full_unstemmed |
Screening for Cognitive Impairment in Parkinson's Disease: Improving the Diagnostic Utility of the MoCA through Subtest Weighting. |
title_sort |
screening for cognitive impairment in parkinson's disease: improving the diagnostic utility of the moca through subtest weighting. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2016-01-01 |
description |
BACKGROUND:Given the high prevalence of cognitive impairment in Parkinson's disease (PD), cognitive screening is important in clinical practice. The Montreal Cognitive Assessment (MoCA) is a frequently used screening test in PD to detect mild cognitive impairment (PD-MCI) and Parkinson's disease dementia (PD-D). However, the proportion in which the subtests are represented in the MoCA total score does not seem reasonable. We present the development and preliminary evaluation of an empirically based alternative scoring system of the MoCA which aims at increasing the overall diagnostic accuracy. METHODS:In study 1, the MoCA was administered to 40 patients with PD without cognitive impairment (PD-N), PD-MCI, or PD-D, as defined by a comprehensive neuropsychological test battery. The new MoCA scoring algorithm was developed by defining Areas under the Curve (AUC) for MoCA subtests in a Receiver Operating Characteristic (ROC) and by weighting the subtests according to their sensitivities and specificities. In study 2, an independent sample of 24 PD patients (PD-N, PD-MCI, or PD-D) was tested with the MoCA. In both studies, diagnostic accuracy of the original and the new scoring procedure was calculated. RESULTS:Diagnostic accuracy increased with the new MoCA scoring algorithm. In study 1, the sensitivity to detect cognitive impairment increased from 62.5% to 92%, while specificity decreased only slightly from 77.7% to 73%; in study 2, sensitivity increased from 68.8% to 81.3%, while specificity stayed stable at 75%. CONCLUSION:This pilot study demonstrates that the sensitivity of the MoCA can be enhanced substantially by an empirically based weighting procedure and that the proposed scoring algorithm may serve the MoCA's actual purpose as a screening tool in the detection of cognitive dysfunction in PD patients better than the original scoring of the MoCA. Further research with larger sample sizes is necessary to establish efficacy of the alternate scoring system. |
url |
http://europepmc.org/articles/PMC4954721?pdf=render |
work_keys_str_mv |
AT sophiefengler screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT josefkessler screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT larstimmermann screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT alexandrazapf screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT saskiaelben screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT larswojtecki screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT olivertucha screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting AT elkekalbe screeningforcognitiveimpairmentinparkinsonsdiseaseimprovingthediagnosticutilityofthemocathroughsubtestweighting |
_version_ |
1725021493382873088 |