Grant Number:	5R01CA226080-04 Interpret this number
Primary Investigator:	Kesler, Shelli
Organization:	University Of Texas At Austin
Project Title:	Predicting Long-Term Chemotherapy-Related Cognitive Impairment
Fiscal Year:	2022

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.




Identifying Themes for Assessing Cancer-Related Cognitive Impairment: Topic Modeling and Qualitative Content Analysis of Public Online Comments.
Authors: Kesler S.R. , Henneghan A.M. , Thurman W. , Rao V. .
Source: JMIR cancer, 2022-05-25; 8(2), p. e34828.
EPub date: 2022-05-25.
PMID: 35612878
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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, 2022 05; 12(4), p. 385-397.
EPub date: 2021-09-03.
PMID: 34210168
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Neurocognitive Impairment After Hematopoietic Stem Cell Transplant for Hematologic Malignancies: Phenotype and Mechanisms.
Authors: Harrison R.A. , Sharafeldin N. , Rexer J.L. , Streck B. , Petersen M. , Henneghan A.M. , Kesler S.R. .
Source: The oncologist, 2021 11; 26(11), p. e2021-e2033.
EPub date: 2021-07-12.
PMID: 34156729
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Brain Imaging in Pediatric Cancer Survivors: Correlates of Cognitive Impairment.
Authors: Kesler S.R. , Sleurs C. , McDonald B.C. , Deprez S. , van der Plas E. , Nieman B.J. .
Source: Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2021-06-01; 39(16), p. 1775-1785.
EPub date: 2021-04-22.
PMID: 33886371
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The association of genetic polymorphisms with neuroconnectivity in breast cancer patients.
Authors: Harrison R.A. , Rao V. , Kesler S.R. .
Source: Scientific reports, 2021-03-17; 11(1), p. 6169.
EPub date: 2021-03-17.
PMID: 33731765
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Measuring Self-Reported Cancer-Related Cognitive Impairment: Recommendations from the Cancer Neuroscience Initiative Working Group.
Authors: Henneghan A.M. , Van Dyk K. , Kaufmann T. , Harrison R. , Gibbons C. , Heijnen C. , Kesler S.R. .
Source: Journal of the National Cancer Institute, 2021-02-26; , .
EPub date: 2021-02-26.
PMID: 33638633
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Cross-Sectional Characterization of Local Brain Network Connectivity Pre and Post Breast Cancer Treatment and Distinct Association With Subjective Cognitive and Psychological Function.
Authors: Kesler S.R. , Tang T. , Henneghan A.M. , Wright M. , Gaber M.W. , Palesh O. .
Source: Frontiers in neurology, 2021; 12, p. 746493.
EPub date: 2021-10-29.
PMID: 34777216
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Does circadian rhythm influence gastrointestinal toxicity?
Authors: Hofmeister E.N. , Fisher S. , Palesh O. , Innominato P.F. .
Source: Current opinion in supportive and palliative care, 2020 06; 14(2), p. 120-126.
PMID: 32332211
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Predicting Patient Reported Outcomes of Cognitive Function Using Connectome-Based Predictive Modeling in Breast Cancer.
Authors: Henneghan A.M. , Gibbons C. , Harrison R.A. , Edwards M.L. , Rao V. , Blayney D.W. , Palesh O. , Kesler S.R. .
Source: Brain topography, 2020 01; 33(1), p. 135-142.
EPub date: 2019-11-19.
PMID: 31745689
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