Predicting Patient Reported Outcomes of Cognitive Function Using Connectome-Based Predictive Modeling in Breast Cancer. Brain topography Henneghan, A. M., Gibbons, C., Harrison, R. A., Edwards, M. L., Rao, V., Blayney, D. W., Palesh, O., Kesler, S. R. 2019

Abstract

Being able to predict who will likely experience cancer related cognitive impairment (CRCI) could enhance patient care and potentially reduce economic and human costs associated with this adverse event. We aimed to determine if post-treatment patient reported CRCI could also be predicted from baseline resting state fMRI in patients with breast cancer. 76 newly diagnosed patients (n?=?42 planned for chemotherapy; n?=?34 not planned for chemotherapy) and 50 healthy female controls were assessed at 3 times points [T1 (prior to treatment); T2 (1 month post chemotherapy); T3 (1 year after T2)], and at yoked intervals for controls. Data collection included self-reported executive dysfunction, memory function, and psychological distress and resting state fMRI data converted to connectome matrices for each participant. Statistical analyses included linear mixed modeling, independent t tests, and connectome-based predictive modeling (CPM). Executive dysfunction increased over time in the chemotherapy group and was stable in the other two groups (p? ?0.31, p?

View details for DOI 10.1007/s10548-019-00746-4

View details for PubMedID 31745689