This is the processed data for the manuscript Outcomes of a computer-based cognitive training (CoRe) in early phases of cognitive decline: a data-driven cluster analysis. Dataset evaluated how patients’ baseline cognitive functioning could be associated to different individual characteristics and different trends of functioning across the cognitive rehabilitation process with CoRe. Identifying such predictors of responsiveness could promote to the development of a “personalized” or “stratified” precision medicine in the context of the broad spectrum of CT interventions. To this end, we used an unsupervised clustering technique in order to find subgroups of patients with different cognitive profiles and study how these clusters respond to the cognitive treatment. Cognitive profiles were developed by considering participants’ global cognition and processing speed (PS). Fifty-seven subjects underwent to a computer-based cognitive training (CCT) for 3 weeks and were evaluated at baseline (T0), post-intervention (T1), and after 6 (T2) and 12 (T3) months. Clusters of cognitive profiles were explored with k-means analysis. The analysis revealed two clusters, which were composed by 27 and 30 patients characterized by lower (Cluster 1) and higher (Cluster 2) cognitive functioning. At T1, cognitive performance improved in both groups, but Cluster 1 gained more benefits in global cognitive functioning than Cluster 2. However, at T3, Cluster 2 remained stable in its clinical condition, whereas Cluster 1 showed a pronounced worsening. In conclusion, Cluster 1 profile was associated with a more marked but also short-lasting responsiveness to CCT, whereas patients fitting with Cluster 2 characteristics seemed to obtain more CCT benefits in terms of stability or even delay of cognitive/functional decline. These findings may have relevant implications in informing the timing and modality of delivery of CCT.

Funding: Ricerca Corrente 2017-2019 Ministry of Health (Italy); European Union's Horizon 2020