Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults

Paula T. Trzepacz, Helen Hochstetler, Shufang Wang, Brett Walker, Andrew J. Saykin

Research output: Contribution to journalArticle

131 Citations (Scopus)

Abstract

Background: The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores. Methods: For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Results: Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥17 on MoCA (96.3 %) and ≥24 on MMSE (98.3 %). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1 %) versus MMSE (71.4 %). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3 %) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. Conclusions: MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

Original languageEnglish (US)
Article number107
JournalBMC Geriatrics
Volume15
Issue number1
DOIs
StatePublished - Sep 7 2015

Fingerprint

Dementia
Alzheimer Disease
Cognitive Dysfunction
ROC Curve
Executive Function
Neuroimaging
Cross-Sectional Studies
Logistic Models
Databases
Surveys and Questionnaires

ASJC Scopus subject areas

  • Geriatrics and Gerontology

Cite this

Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults. / Trzepacz, Paula T.; Hochstetler, Helen; Wang, Shufang; Walker, Brett; Saykin, Andrew J.

In: BMC Geriatrics, Vol. 15, No. 1, 107, 07.09.2015.

Research output: Contribution to journalArticle

@article{20b757c700414cf6b8a2b655896fc2cf,
title = "Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults",
abstract = "Background: The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores. Methods: For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Results: Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥17 on MoCA (96.3 {\%}) and ≥24 on MMSE (98.3 {\%}). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1 {\%}) versus MMSE (71.4 {\%}). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3 {\%}) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. Conclusions: MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.",
author = "Trzepacz, {Paula T.} and Helen Hochstetler and Shufang Wang and Brett Walker and Saykin, {Andrew J.}",
year = "2015",
month = "9",
day = "7",
doi = "10.1186/s12877-015-0103-3",
language = "English (US)",
volume = "15",
journal = "BMC Geriatrics",
issn = "1471-2318",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults

AU - Trzepacz, Paula T.

AU - Hochstetler, Helen

AU - Wang, Shufang

AU - Walker, Brett

AU - Saykin, Andrew J.

PY - 2015/9/7

Y1 - 2015/9/7

N2 - Background: The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores. Methods: For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Results: Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥17 on MoCA (96.3 %) and ≥24 on MMSE (98.3 %). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1 %) versus MMSE (71.4 %). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3 %) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. Conclusions: MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

AB - Background: The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores. Methods: For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Results: Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥17 on MoCA (96.3 %) and ≥24 on MMSE (98.3 %). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1 %) versus MMSE (71.4 %). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3 %) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. Conclusions: MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

UR - http://www.scopus.com/inward/record.url?scp=84940852013&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84940852013&partnerID=8YFLogxK

U2 - 10.1186/s12877-015-0103-3

DO - 10.1186/s12877-015-0103-3

M3 - Article

C2 - 26346644

AN - SCOPUS:84940852013

VL - 15

JO - BMC Geriatrics

JF - BMC Geriatrics

SN - 1471-2318

IS - 1

M1 - 107

ER -