Developing digital biomarker for predicting cognitive response to multi-domain intervention
Abstract
Abstract Computerized cognitive training allows real-time tracking of performance metrics that may serve as digital biomarkers. This study investigated the value of a novel in-game digital biomarker, RTACC (Reaction Time-Accuracy Correlation), the correlation between reaction time and accuracy, using data from 130 participants with mild cognitive impairment enrolled in the intervention arm of the SUPERBRAIN-MEET randomized controlled trial. Participants underwent a 24-week multi-domain intervention, consisting of computerized cognitive training, physical exercise, nutritional education, vascular/metabolic risk management, and motivation enhancement. RTACC was derived from task-level RT and accuracy and examined in relation to cognitive and biomarker outcomes. Linear regression analysis revealed a significant association between RTACC and changes in Repeatable Battery for the Assessment of Neuropsychological Status scores from baseline to 24 weeks (beta coefficient = -11.90 ± 3.78, T = − 3.14, P = 0.002). RTACC also showed a marginal effect on changes in brain-derived neurotrophic factor levels (beta coefficient = − 3.13 ± 1.64, P = 0.057). Logistic regression analysis demonstrated that RTACC combined with clinical information identified good responders with an area under the receiver operating characteristic curve of 0.73 (95% CI: 0.62–0.84). These findings suggest that this in-game digital biomarker (RTACC) may help identify individuals likely to benefit from multi-domain intervention.
Article Details
Authors (10)
Ji Hyeun Park
Hyun Sook Kim
Seong Hye Choi
Department of Neurology, Inha University College of Medicine
Jee Hyang Jeong
So Young Moon
Department of Neurology, Ajou University School of Medicine
Yoo Kyoung Park
Chang Hyung Hong
Department of Psychiatry, Ajou University School of Medicine
Soo Hyun Cho
Department of Neurology, Chonnam National University Medical School, Chonnam National University Hospital
Hae Ri Na
Hang-Rai Kim