Can a tablet-based cancellation test identify cognitive impairment in older adults?

Abstract

There has been a growing interest in using computerized cognitive assessment to detect age-related cognitive disorders. We have developed a tablet-based cancellation test (e-CT), previously shown as a reliable measure of executive functions and free of effect of familiarity with computer-based devices in healthy older adults. This study aimed to investigate the influence of demographics and current daily use of computer-based devices in older adults with Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). We further studied the ability of the e-CT to discriminate MCI and AD patients from older adults with normal cognition (NC).The e-CT was administered to 325 older adults (NC = 112, MCI = 129, AD = 84). Subjects also performed the K-T test, a paper-and-pencil cancellation test from which the e-CT was developed. Multiple linear regression analyses were conducted to assess the contribution of demographics and current daily use of computer-based devices on the e-CT in patient groups. The Receiver Operating Characteristic (ROC) curves and the Area Under the Curve (AUC) were established to compare the efficacy of the e-CT and the K-T test to classify subjects into diagnostic groups.In the MCI group, age (B = -0.37, p<0.001) and current daily use of computer-based devices (B = 5.85, p<0.001) were associated with the number of correct cancellations of the e-CT. In the AD group, only current daily use of a computer-based device was a significant contributor (B = 6.28, p<0.001). The e-CT (AUC = 0.811; 95% confidence interval [CI]: 0.756-0.867) and the K-T (AUC = 0.837; CI: 0.787-0.887) showed good and comparable diagnostic accuracy to discriminate between MCI and NC subjects. To discriminate between NC and AD, both tests showed high diagnostic accuracy, with the AUC values of 0.923 (CI: 0.876-0.971) and 0.929 (95%CI: 0.886-0.972) for the e-CT and the K-T, respectively.The e-CT presents satisfying discriminative validity and is a promising tool for detection of early cognitive impairment in older adults.