权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Mechanistic Risk Prediction of Radiation Therapy Cardiotoxicity

放射治疗心脏毒性的机制风险预测

基本信息

批准号：
10217238
负责人：
Bonnie Ky
金额：
$ 72.82万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-15 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10217238
关键词：
Address Affect Biological Biological Markers Cancer Control Cancer Etiology Cancer Patient Cardiac Cardiomyopathies Cardiotoxicity Cardiovascular Physiology Cardiovascular system Cessation of life Chest Clinical Cohort Studies Collaborations Coronary heart disease Data Disease Dose Functional disorder Heart Heart failure High Prevalence Hospitals Image In Vitro Individual Inflammation Intervention Longitudinal cohort Malignant Neoplasms Malignant neoplasm of lung Measures Methods Microvascular Dysfunction Morbidity - disease rate Multicenter Studies Non-Small-Cell Lung Carcinoma Oncology Outcome Oxidative Stress Pathway interactions Patient-Focused Outcomes Patients Pennsylvania Perfusion Phenotype Prospective cohort Radiation Dose Unit Radiation Oncology Radiation Therapy Oncology Group Radiation therapy Radiology Specialty Randomized Clinical Trials Research Priority Risk Role Solid Neoplasm Stress Toxic effect United States National Institutes of Health Universities Vascular Diseases Washington Woman Work cancer survival cardioprotection cardiovascular risk factor chemoradiation circulating biomarkers effective therapy experience high risk imaging biomarker imaging study improved in vivo innovation mortality multidisciplinary patient subsets prognostic value radiation delivery response risk prediction risk stratification

项目摘要

Abstract Lung cancer is both the most common cancer worldwide and the leading cause of cancer death in the US. While radiation therapy (RT) is a highly effective treatment for many cancers, thoracic RT carries an increased risk of cardiovascular (CV) morbidity and mortality that limit critical gains in cancer control and survival. Despite the significance of this problem, we have a limited understanding of how RT results in CV toxicity, and the biologic and functional mechanisms and predictors of CV toxicity in patients. Fundamental questions include: how does RT affect mechanistic biologic and imaging markers of CV toxicity? Which cardiac radiation dose-volume parameters are associated with CV toxicity? Can baseline levels or early changes in biomarkers, imaging measures and radiation-dose volume parameters identify patients at risk of adverse CV clinical outcomes? Our preliminary data suggest thoracic RT results in inflammation, oxidative stress, microvascular dysfunction, and worse CV function in patients. We will extend these findings through detailed characterization of these pathways in a multi-center, longitudinal prospective cohort of nonsmall cell lung cancer patients from the University of Pennsylvania, Washington University, and the Brigham and Women’s Hospital treated with definitive thoracic chemoradiation for curative intent. We focus on lung cancer given the high prevalence of disease, the important role of RT in cancer control, the concomitant CV morbidity and mortality associated with RT, and the high RT doses delivered to the heart. Our overall objective is to determine if RT results in early, subclinical CV dysfunction using highly sensitive, quantitative biologic and functional measures; understand how cardiac dose-volume parameters influence these abnormalities; and develop multi-marker strategies in risk prediction. Our multi- center longitudinal cohort forms the basis of all Aims. In Aim 1, we will evaluate the changes in circulating biomarkers of CV stress, inflammation and vascular dysfunction, and to define the associations with RT dose- volume measures. In Aim 2, we will quantify RT-related changes in imaging-derived measures of CV function and perfusion, and to define the associations with RT dose-volume measures. In Aim 3, we will determine the prognostic value of biologic, imaging, and RT dose-volume measures as indicators of adverse CV outcomes. By using innovative methods in deep CV phenotyping to identify high risk individuals, we will personalize the delivery of RT and targeted cardioprotective interventions, and ultimately improve CV and overall patient outcomes. We will leverage our experiences in precision phenotyping of cancer patients undergoing cardiotoxic therapy to address a high-priority research gap in response to NIH PA 19-112.

摘要