Background Test items in MoCA (Montreal Cognitive Assessment) can be used to generate 5 domain scores (i.e. Memory, Language, Attention, Executive and Visuospatial) which have been shown to approximate well-established neuropsychological tests. As neuropsychological tests are known to be affected by age, sex, education, and language of administration, this study derived a regression-based Z-score calculator for MoCA Domain Scores (MDS) that adjusts individual performance for these key confounders; with the intention of improving the clinical utility of MDS as a proxy for conventional neuropsychological tests. Methods Participants ≥ 50 years were recruited from Alzheimer’s Disease Centers across USA (n = 25,330), and completed MoCA and conventional neuropsychological tests. A subset with normal cognition and global Clinical Dementia Rating of 0 (n = 11,371) was used to derive the Z-score calculator for MDS; while the full sample (n = 25,330) verified the performance of MDS Z-scores in detecting domain-specific impairments (as defined by conventional neuropsychological tests), using areas under the receiver operating characteristic curve (AUC). Results MDS varied significantly by age, sex, education, and language of administration even among participants with normal cognition. Based on age-, sex-, education-, and language-adjusted Z-scores, the respective AUCs were 91.2% for MoCA–Memory (95%CI 90.7–91.6), 83.6% for MoCA–Language (95%CI 83.0–84.3), 88.7% for MoCA–Attention (95%CI 88.0–89.4), 85.5% for MoCA–Executive (95%CI 84.8–86.1), and 81.0% for MoCA–Visuospatial (95%CI 80.2–81.8). At the commonly-used cut-off of Z-scores ≤ -1.50, all the MDS had specificities of ≥ 80%. Conclusions MDS Z-scores can be easily computed using the newly-developed Excel-based calculator, and provide a viable alternative when conventional neuropsychological tests are needed but cannot be feasibly administered, such as in non-specialty clinics with large volume of patients at high-risk of cognitive impairment (e.g. primary-care, geriatric, and stroke-prevention clinics), and, with further validation and calibration, plausibly also in other resource-limited healthcare settings (e.g. in lower- and middle-income countries). They can complement neuropsychological tests as part of the systematic evaluation of cognitive impairment, and help reserve neuropsychological tests for patients most likely to benefit from further evaluation.

A normative calculator for MoCA domain scores: proxy for Z-scores of conventional neuropsychological tests

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2025年7月21日

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Tau Ming Liew

摘要

Background

Test items in MoCA (Montreal Cognitive Assessment) can be used to generate 5 domain scores (i.e. Memory, Language, Attention, Executive and Visuospatial) which have been shown to approximate well-established neuropsychological tests. As neuropsychological tests are known to be affected by age, sex, education, and language of administration, this study derived a regression-based Z-score calculator for MoCA Domain Scores (MDS) that adjusts individual performance for these key confounders; with the intention of improving the clinical utility of MDS as a proxy for conventional neuropsychological tests.

Methods

Participants ≥ 50 years were recruited from Alzheimer’s Disease Centers across USA (n = 25,330), and completed MoCA and conventional neuropsychological tests. A subset with normal cognition and global Clinical Dementia Rating of 0 (n = 11,371) was used to derive the Z-score calculator for MDS; while the full sample (n = 25,330) verified the performance of MDS Z-scores in detecting domain-specific impairments (as defined by conventional neuropsychological tests), using areas under the receiver operating characteristic curve (AUC).

Results

MDS varied significantly by age, sex, education, and language of administration even among participants with normal cognition. Based on age-, sex-, education-, and language-adjusted Z-scores, the respective AUCs were 91.2% for MoCA–Memory (95%CI 90.7–91.6), 83.6% for MoCA–Language (95%CI 83.0–84.3), 88.7% for MoCA–Attention (95%CI 88.0–89.4), 85.5% for MoCA–Executive (95%CI 84.8–86.1), and 81.0% for MoCA–Visuospatial (95%CI 80.2–81.8). At the commonly-used cut-off of Z-scores ≤ -1.50, all the MDS had specificities of ≥ 80%.

Conclusions

MDS Z-scores can be easily computed using the newly-developed Excel-based calculator, and provide a viable alternative when conventional neuropsychological tests are needed but cannot be feasibly administered, such as in non-specialty clinics with large volume of patients at high-risk of cognitive impairment (e.g. primary-care, geriatric, and stroke-prevention clinics), and, with further validation and calibration, plausibly also in other resource-limited healthcare settings (e.g. in lower- and middle-income countries). They can complement neuropsychological tests as part of the systematic evaluation of cognitive impairment, and help reserve neuropsychological tests for patients most likely to benefit from further evaluation.