Understanding and Predicting Fatigue, CV Decline & Events After Breast CA Treatment

了解和预测疲劳、CV 下降

基本信息

批准号：
10481826
负责人：
William Gregory Hundley
金额：
$ 21.29万
依托单位：
WAKE FOREST UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2024-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10481826
关键词：
Acute Address Adjuvant Adjuvant Chemotherapy Adjuvant Therapy Age American Heart Association Anthracycline Behavioral Biological Markers Breast Breast Cancer Patient Breast Cancer Treatment Breast Cancer survivor Breast Cancer therapy Cancer Survivor Cardiac Death Cardiopulmonary Cardiotoxicity Cardiovascular Diseases Cardiovascular Physiology Cardiovascular system Categories Chronic Disease Clinical Cohort Studies Communities Community Clinical Oncology Program Community Hospitals Consumption Data Databases Development EFRAC Early Diagnosis Echocardiography Enrollment Epidemiology Equation Ethnic Origin Etiology Event Exercise Test FarGo Fatigue Fibrosis Functional disorder Funding Future Guidelines Healthcare Heart failure Image Impairment Incidence Inflammation Infrastructure Intervention Knowledge Left Left Ventricular Dysfunction Left Ventricular Ejection Fraction Left Ventricular Function Life Longitudinal Studies Magnetic Resonance Imaging Malignant Neoplasms Measures Mediating Mental Health Modeling Morbidity - disease rate Multicenter Studies Myocardial Myocardial Infarction Natural History Neoadjuvant Therapy Network-based Patient Self-Report Patients Physiologic pulse Population Preventive Quality of life Race Radiation Radiation therapy Research Research Design Research Personnel Risk Risk Factors SF-36 Savings Schedule Secure Serum Structure Surveillance Program Survival Rate Survivors Thick Time Toxic effect Ventricular Walking Woman base breast cancer diagnosis cancer therapy cardiovascular injury cardiovascular risk factor chemotherapy clinical center cohort cost design detection method exercise capacity exercise intolerance experience forest health related quality of life high risk hospital utilization improved malignant breast neoplasm mortality normal aging physical conditioning prediction algorithm predictive modeling prevent programs prospective psychosocial public health relevance risk prediction therapy design

项目摘要

DESCRIPTION (provided by applicant): Though the use of chemotherapy and early detection methods have greatly increased survival rates for women with Stage I-III breast cancer, this progress is threatened by a significant increase in cardiovascular (CV) events for survivors. Over 35% of women experience CV injury, left ventricular (LV) dysfunction, exercise intolerance, or fatigue after receipt of adjuvant chemotherapy (Adj-C) for Stage I-III breast cancer. In addition, CV events are the leading cause of morbidity and mortality for those surviving 5 to 8 years after their breast cancer diagnosis. Currently, little is understood about te origins of CV dysfunction, exercise intolerance, or fatigue in these women, and risk prediction algorithms for CV events do not incorporate breast cancer treatment in their models. We propose a study of baseline and serial longitudinal measures that will determine the influence of Adj-C with and without concomitant radiation treatment on 3 general categories: (1) CV function, (2) exercise capacity and fatigue, and (3) future development of CV events in a cohort of 1,000 women (840 with Stage I-III Breast Cancer and 160 healthy comparators). We also seek to answer questions about the relationship of alterations in LV and aortic function, what demographic risk factors and changes in serum biomarkers precede LV dysfunction, and if risk factor prediction models forecast development of CV events in the same cohort. Our longitudinal study design accounts for pre-existing and dynamic changes in risk factors during receipt of Adj-C and assesses subsequent CV events. This study has secured robust financial and infrastructure support through the Wake Forest NCI Community Oncology Research Program. This partnership reduces the overall cost of the current proposal by funding enrollment, staff reimbursement, regulatory oversight, study database development, echocardiograms, and an active surveillance program to ascertain the occurrence of CV events. This will be the first epidemiologic cohort study designed to fully characterize the time course and define the correlates of subclinical CV dysfunction, exercise intolerance, fatigue and CV events in women treated with Adj-C for breast cancer. A study of this magnitude is important to assess a variety of subjects so that the scientific community may better understand who is at risk and how we can prevent future CV damage. By enrolling patients in community hospitals and utilizing the unique expertise of each Co-Investigator, this study can capture the data needed to make such predictions. The immediate impact of this research will reduce the gaps in knowledge that prevent treatment design and generate risk prediction algorithms to avert CV events in breast cancer survivors. New knowledge from this study will quantify the risk of developing subclinical CV disease and exercise intolerance in this population, identify potential mechanisms, and inform future study development to reduce CV disease and improve overall survival in women with breast cancer.

描述（由申请人提供）：虽然化疗和早期检测方法的使用大大提高了 I-III 期乳腺癌女性的生存率，但这一进展受到 35 岁以上幸存者心血管 (CV) 事件显着增加的威胁。 % 的女性在接受 I-III 期乳腺癌辅助化疗 (Adj-C) 后出现心血管损伤、左心室 (LV) 功能障碍、运动不耐受或疲劳。此外，心血管事件是发病和死亡的主要原因。为了目前，人们对这些女性的心血管功能障碍、运动不耐受或疲劳的起源知之甚少，并且心血管事件的风险预测算法并未将乳腺癌治疗纳入其模型中。我们提出了一项基线和连续纵向测量的研究，以确定 Adj-C 联合或不联合放射治疗对 3 个一般类别的影响：(1) CV 功能，(2) 运动能力和疲劳，以及 (3) 未来发展一组中的 CV 事件1,000 名女性（840 名患有 I-III 期乳腺癌和 160 名健康对照者）我们还试图回答有关左心室和主动脉功能改变的关系、哪些人口统计学危险因素和血清生物标志物变化先于左心室功能障碍以及是否有风险的问题。我们的纵向研究设计考虑了接受 Adj-C 期间风险因素的预先存在和动态变化，并评估了后续的 CV 事件。通过维克森林国家癌症研究所社区肿瘤学研究计划提供基础设施支持，这种伙伴关系通过资助注册、人员报销、监管监督、研究数据库开发、超声心动图和确定心血管发生情况的主动监测计划，降低了当前提案的总体成本。这将是第一项流行病学队列研究，旨在全面描述接受 Adj-C 治疗乳腺癌的女性的时间过程并确定亚临床心血管功能障碍、运动不耐受、疲劳和心血管事件的相关性。评估各种主题非常重要，以便科学界可以更好地了解谁处于危险之中以及我们如何预防未来的心血管损伤。通过在社区医院招募患者并利用每位联合研究者的独特专业知识，这项研究可以捕获。这项研究的直接影响将缩小阻碍治疗设计的知识差距，并生成风险预测算法来避免乳腺癌幸存者发生心血管事件。心血管疾病和运动不耐受人群，确定潜在机制，并为未来的研究发展提供信息，以减少心血管疾病并提高乳腺癌女性的总体生存率。