Diagnostic Accuracy of Memory Measures in Alzheimer’s Dementia and Mild Cognitive Impairment: a Systematic Review and Meta-Analysis

Abstract

With an increasing focus on biomarkers in dementia research, illustrating the role of neuropsychological assessment in detecting mild cognitive impairment (MCI) and Alzheimer’s dementia (AD) is important. This systematic review and meta-analysis, conducted in accordance with PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) standards, summarizes the sensitivity and specificity of memory measures in individuals with MCI and AD. Both meta-analytic and qualitative examination of AD versus healthy control (HC) studies (n = 47) revealed generally high sensitivity and specificity (≥ 80% for AD comparisons) for measures of immediate (sensitivity = 87%, specificity = 88%) and delayed memory (sensitivity = 89%, specificity = 89%), especially those involving word-list recall. Examination of MCI versus HC studies (n = 38) revealed generally lower diagnostic accuracy for both immediate (sensitivity = 72%, specificity = 81%) and delayed memory (sensitivity = 75%, specificity = 81%). Measures that differentiated AD from other conditions (n = 10 studies) yielded mixed results, with generally high sensitivity in the context of low or variable specificity. Results confirm that memory measures have high diagnostic accuracy for identification of AD, are promising but require further refinement for identification of MCI, and provide support for ongoing investigation of neuropsychological assessment as a cognitive biomarker of preclinical AD. Emphasizing diagnostic test accuracy statistics over null hypothesis testing in future studies will promote the ongoing use of neuropsychological tests as Alzheimer’s disease research and clinical criteria increasingly rely upon cerebrospinal fluid (CSF) and neuroimaging biomarkers.

Enhanced diagnostic accuracy for neurocognitive disorders: a revised cut-off approach for the Montreal Cognitive Assessment

“…Sensitivity, specificity, and the AUC give an indication of the quality of the test under observation by classifying the test performance with respect to a reference standard (i.e., an individual will be classified as a patient on the MoCA as well as according to a complete Memory Clinic diagnostic workup). However, these measures do not inform about the probability whether a tested individual has a specific disease [15,34]. Predictive values-which are influenced by prevalence rates-reflect this information.…”

“…However, the psychometric properties of any screening test are not fixed characteristics, but depend on the clinical context [14], limiting the transferability of these cut-offs to other settings. Moreover, most previous authors defined "optimal cut-offs," which aim at finding the best balance between sensitivity and specificity, as opposed to conventional cut-offs that are based on clinical standards (e.g., test performance 1-2 SD below the normative mean [9,15]). Optimal cut-offs are likely to be sampledependent and specific to the individual study [15,16] and should therefore be validated in independent samples.…”

“…Moreover, most previous authors defined "optimal cut-offs," which aim at finding the best balance between sensitivity and specificity, as opposed to conventional cut-offs that are based on clinical standards (e.g., test performance 1-2 SD below the normative mean [9,15]). Optimal cut-offs are likely to be sampledependent and specific to the individual study [15,16] and should therefore be validated in independent samples. Furthermore, in most validation studies, a rather homogenous patient sample was recruited (e.g., only patients with probable Alzheimer's disease (AD) according to McKhann criteria [17], exclusion of patients with medical comorbidities), which does not reflect the clinical reality, where patient populations are typically heterogeneous, and medical comorbidities are frequent.…”

A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes

“…A third example is drawn from the study of Weissberger et al (2017), who were interested in examining the accuracy of neuropsychological assessments in detecting mild cognitive impairment (MCI) and Alzheimer's dementia (AD). The accuracy of such assessments is usually quantified by the sensitivity and specificity of the tests that are used to make the assessment.…”

“…Abramovitch et al (2018) conducted three separate metaanalyses on Full Scale IQ, Verbal IQ, and Performance IQ. There are several such examples in the literature (e.g., Belleville et al, 2017;Weissberger et al, 2017). This approach is appealing because no new technique needs to be used.…”