Abstract
Purpose: Cancer-related cognitive impairment (CRCI) is a common neurotoxicity among patients with breast and other cancers. Neuroimaging studies have demonstrated measurable biomarkers of CRCI but have largely neglected the potential heterogeneity of the syndrome. Methods: We used retrospective functional MRI data from 80 chemotherapy-treated breast cancer survivors to examine neurophysiologic subtypes or “biotypes” of CRCI. The breast cancer group consisted of training (N = 57) and validation (N = 23) samples. Results: An unsupervised clustering approach using connectomes from the training sample identified three distinct biotypes. Cognitive performance (p < 0.05, corrected) and regional connectome organization (p < 0.001, corrected) differed significantly between the biotypes and also from 103 healthy female controls. We then built a random forest classifier using connectome features to distinguish between the biotypes (accuracy = 91%) and applied this to the validation sample to predict biotype assignment. Cognitive performance (p < 0.05, corrected) and regional connectome organization (p < 0.005, corrected) differed significantly between the predicted biotypes and healthy controls. Biotypes were also characterized by divergent clinical and demographic factors as well as patient reported outcomes. Conclusions: Neurophysiologic biotypes may help characterize the heterogeneity associated with CRCI in a data-driven manner based on neuroimaging biomarkers. Implications for Cancer Survivors: Our novel findings provide a foundation for detecting potential risk and resilience factors that warrant further study. With further investigation, biotypes might be used to personalize assessments of and interventions for CRCI.
Original language | English (US) |
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Pages (from-to) | 483-493 |
Number of pages | 11 |
Journal | Journal of Cancer Survivorship |
Volume | 14 |
Issue number | 4 |
DOIs | |
State | Published - Aug 1 2020 |
Keywords
- Breast Cancer
- Cognition
- Connectome
- MRI
- Machine Learning
ASJC Scopus subject areas
- Oncology
- Oncology(nursing)