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MACE for Diagnosis of Dementia and MCI: Examining Cut-Offs and Predictive Values

Cognitive Function Clinic, Walton Centre for Neurology and Neurosurgery, Liverpool, L9 7LJ, UK
Diagnostics 2019, 9(2), 51;
Received: 28 March 2019 / Revised: 23 April 2019 / Accepted: 1 May 2019 / Published: 6 May 2019
(This article belongs to the Special Issue Diagnosis of Dementia and Cognitive Impairment)
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The definition of test cut-offs is a critical determinant of many paired and unitary measures of diagnostic or screening test accuracy, such as sensitivity and specificity, positive and negative predictive values, and correct classification accuracy. Revision of test cut-offs from those defined in index studies is frowned upon as a potential source of bias, seemingly accepting any biases present in the index study, for example related to sample bias. Data from a large pragmatic test accuracy study examining the Mini-Addenbrooke’s Cognitive Examination (MACE) were interrogated to determine optimal test cut-offs for the diagnosis of dementia and mild cognitive impairment (MCI) using either the maximal Youden index or the maximal correct classification accuracy. Receiver operating characteristic (ROC) and precision recall (PR) curves for dementia and MCI were also plotted, and MACE predictive values across a range of disease prevalences were calculated. Optimal cut-offs were found to be a point lower than those defined in the index study. MACE had good metrics for the area under the ROC curve and for the effect size (Cohen’s d) for both dementia and MCI diagnosis, but PR curves suggested the superiority for MCI diagnosis. MACE had high negative predictive value at all prevalences, suggesting that a MACE test score above either cut-off excludes dementia and MCI in any setting.
Keywords: diagnosis; dementia; mild cognitive impairment; Mini-Addenbrooke’s Cognitive Examination diagnosis; dementia; mild cognitive impairment; Mini-Addenbrooke’s Cognitive Examination
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Larner, A.J. MACE for Diagnosis of Dementia and MCI: Examining Cut-Offs and Predictive Values. Diagnostics 2019, 9, 51.

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