Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer’s Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

Abstract

Background: Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer’s disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD. Objective: We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test. Methods: Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent. Results: A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260). Conclusion: MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.

Bayesian estimation for the accuracy of three neuropsychological tests in detecting Alzheimer's disease and mild cognitive impairment: a retrospective analysis of the ADNI database

“…In addition, the results of this study in the ADNI population are consistent with the findings of previous meta-analyses that investigated the diagnostic performance of the MOCA and MMSE for detecting AD and MCI due to AD under non-gold standard conditions using a hierarchical Bayesian latent class meta-analysis [ 23 , 24 ]. In that study, the MoCA demonstrated a sensitivity of 0.934 and a specificity of 0.899 in detecting AD, while the MMSE had a sensitivity of 0.883 and a specificity of 0.903 [ 23 ]. For the detection of MCI, the MoCA showed a sensitivity of 0.85 and a specificity of 0.79, whereas the MMSE had a sensitivity of 0.71 and a specificity of 0.71 [ 24 ].…”

“…We obtained the priors for sensitivity and specificity of each test by previous literatures [ 23 – 25 ], and the priors for prevalence of AD and MCI due to AD were from review reports [ 1 , 5 ]. The specific details of informative prior distributions for the parameters in the models are presented in Table 3 .…”

The dementia severity rating scale: A potential community screening tool for dementia in low- and middle-income countries

“…These cognitive measures can also be time-consuming, not education-fair, not culturally-fair, and may need well-trained interviewers to ensure standardized and reliable outcomes ( Baldo et al, 2013 ; Li et al, 2012 ; Nasreddine et al, 2004 ; Turana & Handajani, 2011 ). Measures such as the MMSE and MoCA demonstrate good screening properties for Alzheimer’s disease (AD), however, language, educational attainment, literacy, and country of study introduces significant sources of heterogeneity and error ( Wang et al, 2022 ).…”