Grant Number:	5R01CA226080-06 Interpret this number
Primary Investigator:	Kesler, Shelli
Organization:	University Of Texas At Austin
Project Title:	Predicting Long-Term Chemotherapy-Related Cognitive Impairment
Fiscal Year:	2024

ABSTRACT 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.




Evidence of compensatory neural hyperactivity in a subgroup of chemotherapy-treated breast cancer survivors and its association with brain aging.
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Source: Medrxiv : The Preprint Server For Health Sciences, 2024-04-22 00:00:00.0; , .
EPub date: 2024-04-22 00:00:00.0.
PMID: 38712178
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Cancer-related cognitive impairment in racial and ethnic minority groups: a scoping review.
Authors: Franco-Rocha O.Y. , Lewis K.A. , Longoria K.D. , De La Torre Schutz A. , Wright M.L. , Kesler S.R. .
Source: Journal Of Cancer Research And Clinical Oncology, 2023-07-11 00:00:00.0; , .
EPub date: 2023-07-11 00:00:00.0.
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Authors: Mulholland M.M. , Prinsloo S. , Kvale E. , Dula A.N. , Palesh O. , Kesler S.R. .
Source: Brain Imaging And Behavior, 2023-05-02 00:00:00.0; , .
EPub date: 2023-05-02 00:00:00.0.
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Authors: Kesler S.R. , Henneghan A.M. , Prinsloo S. , Palesh O. , Wintermark M. .
Source: Frontiers In Medicine, 2023; 10, p. 1199605.
EPub date: 2023-08-29 00:00:00.0.
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Subjective cancer-related cognitive impairments and salience network connectivity in breast cancer survivors.
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Source: Journal Of Cancer Survivorship : Research And Practice, 2022-12-05 00:00:00.0; , .
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Source: Cancer Medicine, 2022-10-11 00:00:00.0; , .
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Changes in Brain Functional and Effective Connectivity After Treatment for Breast Cancer and Implications for Intervention Targets.
Authors: Phillips N.S. , Rao V. , Kmetz L. , Vela R. , Medick S. , Krull K. , Kesler S.R. .
Source: Brain Connectivity, 2021-09-03 00:00:00.0; , .
EPub date: 2021-09-03 00:00:00.0.
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Brain Imaging in Pediatric Cancer Survivors: Correlates of Cognitive Impairment.
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Source: Journal Of Clinical Oncology : Official Journal Of The American Society Of Clinical Oncology, 2021-06-01 00:00:00.0; 39(16), p. 1775-1785.
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The association of genetic polymorphisms with neuroconnectivity in breast cancer patients.
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