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. Therefore, we measured the connectome is patients prior to any treatment and demonstrated that these connectome properties could be used in combination with machine learning to predict 1 year post-chemotherapy cognitive impairment with 100% accuracy. The proposed project aims to test this preliminary 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 yoked intervals. We will combine these data with retrospective data we obtained during a prior study for a total sample of 150 in each group. 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- related and medical variables alone. We will also examine longitudinal changes in connectome organization associated with impairment subtypes (i.e. persistent vs. late onset impairment) as well as changes in specific functional networks (e.g. default mode, salience, executive-attention and sensory- motor networks). This information will provide novel insights regarding the neural mechanisms of CRCI and may also help us refine our prediction models.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA226080-01A1
Application #
9661149
Study Section
Adult Psychopathology and Disorders of Aging Study Section (APDA)
Program Officer
Horowitz, Todd S
Project Start
2019-05-01
Project End
2024-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Texas Austin
Department
Type
Schools of Nursing
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78759