Chemotherapy-related cognitive impairment (CRCI) affects an estimated 60% of patients, negatively impacting quality of life. Currently, there is no established method for predicting which patients will develop CRCI.This information could be practice-changing by assisting clinicians with treatment decision-making for individual patients.
We have shown that the brain network (“connectome”) is significantly altered in patients with CRCI. In an earlier study, we measured the connectome in patients prior to any treatment and showed that these brain network properties could be used in combination with machine learning to predict 1 year post-chemotherapy cognitive impairment with 100% accuracy.
he proposed project aims to test this prediction model in a new, larger sample with the overarching goal of validating its use for clinical practice. We will enroll 100 newly diagnosed patients with primary breast cancer scheduled for adjuvant chemotherapy who will be assessed prior to any treatment, including surgery with general anesthesia, 1 month after chemotherapy treatment and again 1 year later. We will also enroll matched healthy female controls who will be assessed at the same time points.
Data from healthy controls will be used to determine impairment status in patients with breast cancer and to provide a template of typical connectome organization for comparison.
We hypothesize that our machine learning model will accurately predict 1 year post- chemotherapy cognitive impairment and that it will be more accurate than a model that includes patient history and medical information alone. We will also examine the changes in brain networks over time. This information will provide novel insights regarding the neural mechanisms of CRCI and may also help us refine our prediction models.
A significant proportion of women who receive chemotherapy for breast cancer will experience long- term problems with brain function, such as thinking, memory and attention that reduce quality of life and extend disease-related disability. The proposed study aims to validate a model for predicting who will develop long-term cognitive impairment and to examine the underlying causes of this impairment. This research is highly relevant to breast cancer, one of the most common public health problems, affecting 1 in 8 women.