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Sensitivity and specificity of the CANTAB Paired Associates Learning test for identifying mild cognitive impairment
Yashar Nabizadeh1, Malihe Talebi2, Elnaz Gholipour-Khalili3
1Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.
Abstract:
Mild cognitive impairment (MCI) is a stage between normal cognition and dementia, and timely diagnosis of this condition offers the opportunity for effective interventions to slow down the progression to dementia. The Mini-Mental Status Exam (MMSE) and the Montreal Cognitive Assessment (MoCA) are widely used tests for MCI screening. The Cambridge Neuropsychological Test Automated Battery (CANTAB) is a computer-based cognitive battery designed to reduce the influence of language and the possibility of examiner error. This study aimed to investigate the diagnostic accuracy of CANTAB in patients with MCI. Patients with a MoCA score of 25 or less were considered to be in the MoCA-defined MCI group, which comprised 23.1% of participants (15 out of 65). The Paired Associates Learning (PAL)-mean-error-to-success had the most area under the curve in the ROC curve (0.80; 95%CI: 0.66-0.95; p-value<0.01) and optimum cut-off for MCI diagnosis was 5.8 (Sensitivity: 77%; Specificity: 74%) based on the Youden index. Although the small sample size may have influenced the results, the findings suggest that the PAL demonstrated good diagnostic accuracy for distinguishing participants with MoCA-defined MCI.
Insights
The Paired Associates Learning (PAL) test from the Cambridge Neuropsychological Test Automated Battery (CANTAB) shows promise for diagnosing mild cognitive impairment (MCI). This computer-based test accurately identified individuals with MCI, offering a potential tool for early detection.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Gerontology
Background:
- Mild cognitive impairment (MCI) represents a transitional stage between normal aging and dementia.
- Early identification of MCI is crucial for implementing interventions that may slow dementia progression.
- Standard screening tools like the Mini-Mental Status Exam (MMSE) and Montreal Cognitive Assessment (MoCA) are widely used but can be influenced by language and examiner variability.
Purpose of the Study:
- To evaluate the diagnostic accuracy of the Cambridge Neuropsychological Test Automated Battery (CANTAB) for identifying mild cognitive impairment (MCI).
- To assess the performance of specific CANTAB tests in distinguishing individuals with MCI from those without.
Main Methods:
- A cohort of participants was screened for MCI using the Montreal Cognitive Assessment (MoCA), with scores ≤ 25 defining the MCI group.
- The diagnostic accuracy of various CANTAB tests was analyzed using receiver operating characteristic (ROC) curves.
- The Paired Associates Learning (PAL) test's mean error to success metric was specifically examined for its diagnostic utility.
Main Results:
- The Paired Associates Learning (PAL)-mean-error-to-success demonstrated the highest area under the curve (0.80) in ROC analysis, indicating significant diagnostic power.
- An optimal cut-off score of 5.8 for the PAL test yielded a sensitivity of 77% and a specificity of 74% for MCI detection.
- The PAL test showed good diagnostic accuracy in identifying individuals classified with MCI based on MoCA scores.
Conclusions:
- The Paired Associates Learning (PAL) component of the CANTAB exhibits notable diagnostic accuracy for mild cognitive impairment (MCI).
- CANTAB, particularly the PAL test, offers a potentially valuable, computer-administered tool for objective MCI screening, minimizing language and examiner bias.
- Further research with larger sample sizes is warranted to confirm these findings and establish the clinical utility of CANTAB in MCI diagnosis.
