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

了解和预测疲劳、CV 下降

• 批准号: 9124809
• 负责人: William Gregory Hundley
• 金额: $ 63.89万
• 依托单位: WAKE FOREST UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9124809
• 关键词: Accounting; Acute; Address; Adjuvant; Adjuvant Chemotherapy; Adjuvant Therapy; Age; American Heart Association; Anthracyclines; Behavioral; Biological Markers; Breast; Breast Cancer Patient; Breast Cancer Treatment; Breast Cancer survivor; 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 stress test; FarGo; Fatigue; Fibrosis; Functional disorder; Funding; Future; Guidelines; Health; Healthcare; Heart failure; Image; Incidence; Inflammation; Intervention; Knowledge; Left; Left Ventricular Dysfunction; Left Ventricular Ejection Fraction; Left Ventricular Function; Life; Longitudinal Studies; Magnetic Resonance Imaging; Malignant Neoplasms; Maps; Measures; Mediating; Mental Health; Methods; Modeling; Morbidity - disease rate; Multicenter Studies; Myocardial; Myocardial Infarction; Natural History; Network-based; Patient Self-Report; Patients; Physiologic pulse; Population; Preventive; Quality of life; Race; Radiation; Radiation therapy; Research; Research Design; Research Infrastructure; Research Personnel; Risk; Risk Factors; SF-36; Schedule; Secure; Serum; Staging; 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; cohort; cost; design; exercise capacity; exercise intolerance; experience; forest; health related quality of life; high risk; improved; malignant breast neoplasm; mortality; normal aging; physical conditioning; prediction algorithm; prevent; programs; prospective; psychosocial; therapy design

 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）：虽然使用化疗和早期检测方法大大提高了I-III期乳腺癌女性的生存率，但这一进展受到幸存者心血管（CV）事件显著增加的威胁。超过35%的女性在接受I-III期乳腺癌的辅助化疗（化疗-C）后经历CV损伤、左心室（LV）功能障碍、运动不耐受或疲劳。此外，CV事件是乳腺癌诊断后存活5 - 8年的患者发病和死亡的主要原因。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，心血管事件的风险预测算法在其模型中没有纳入乳腺癌治疗。我们提出了一项基线和系列纵向测量的研究，将在1,000名女性（840名I-III期乳腺癌患者和160名健康对照者）的队列中确定联合和不联合放疗的TAC-C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）CV事件的未来发展。 我们还试图回答有关左心室和主动脉功能改变之间的关系，什么样的人口统计学风险因素和血清生物标志物的变化先于左心室功能障碍，以及风险因素预测模型是否预测同一队列中CV事件的发展等问题。我们的纵向研究设计考虑了在接受抗-HCV治疗期间风险因素的预先存在和动态变化，并评估了随后的CV事件。这项研究通过维克森林NCI社区肿瘤学研究计划获得了强大的财政和基础设施支持。这种伙伴关系通过资助入组、员工报销、监管监督、研究数据库开发、超声心动图和主动监测计划来确定CV事件的发生，从而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，旨在充分描述时间进程，并确定接受TMA-C治疗乳腺癌的女性亚临床CV功能障碍、运动不耐受、疲劳和CV事件的相关性。这种规模的研究对于评估各种受试者非常重要，以便科学界可以更好地了解谁处于风险中以及我们如何预防未来的CV损伤。通过在社区医院招募患者并利用每位合作研究者的独特专业知识，本研究可以捕获进行此类预测所需的数据。这项研究的直接影响将减少阻止治疗设计的知识差距，并生成风险预测算法，以避免乳腺癌幸存者的CV事件。这项研究的新知识将量化该人群中发生亚临床CV疾病和运动不耐受的风险，确定潜在的机制，并为未来的研究开发提供信息，以减少CV疾病并改善乳腺癌女性的总生存期。