Risk prediction of breast cancer treatment-related cardiotoxicity to guide clinical decision making

乳腺癌治疗相关心脏毒性的风险预测以指导临床决策

基本信息

批准号：
10191034
负责人：
Reina Haque
金额：
$ 37.82万
依托单位：
KAISER FOUNDATION RESEARCH INSTITUTE
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：
2020-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10191034
关键词：
Acute myocardial infarction Address Adjuvant Adjuvant Chemotherapy Adjuvant Therapy Adoption Adult Affect Aftercare Age Aging Antidiabetic Drugs Antihypertensive Agents Biological Products Body mass index Breast Cancer Risk Factor Breast Cancer Treatment Breast Cancer survivor Breast Cancer therapy California Cancer Control Cardiology Cardiomyopathies Cardiotoxicity Cardiovascular Diseases Cardiovascular system Caring Cause of Death Cessation of life Characteristics Cholesterol Clinical Combined Modality Therapy Communities Data Diabetes Mellitus Diagnosis Early Diagnosis Electronic Health Record Ethnic Origin Event General Population Guidelines Health Heart failure High Risk Woman Hormonal Hospitals Hyperlipidemia Hypertension Impaired health Individual Intervention Lead Length Life Expectancy Life Style Modification Link Longitudinal cohort study Low income Malignant Neoplasms Managed Care Measures Medicare/Medicaid Modeling Monitor Morbidity - disease rate Myocardial Ischemia National Cancer Institute National Heart, Lung, and Blood Institute Newly Diagnosed Oncology Outcome Patient Care Persons Pharmaceutical Preparations Practice Guidelines Prevention Preventive Prognosis Public Health Quality of life Race Radiation Radiation therapy Records Reporting Risk Risk Estimate Risk Factors Smoking Societies Stroke Survivors Toxic effect Transient Ischemic Attack Treatment-Related Cancer Uncertainty Woman Work World Health alternative treatment base burden of illness cancer diagnosis cancer therapy cardioprotection cardiovascular disorder prevention cardiovascular disorder risk cardiovascular imaging cardiovascular risk factor cerebrovascular chemotherapy clinical decision-making clinical practice cohort ethnic minority population evidence base follow-up health care settings health plan health related quality of life high risk hormone therapy malignant breast neoplasm member mortality predictive modeling premature preservation programs racial and ethnic risk prediction risk prediction model routine imaging socioeconomics standard care treatment planning treatment risk treatment strategy tumor venous thromboembolism

项目摘要

PROJECT SUMMARY Nearly 20% of the 3 million breast cancer survivors in the U.S. have cardiovascular disease (CVD). The National Cancer Institute, NHLBI, and professional oncology and cardiology societies have all endorsed the importance of reducing CVD burden in breast cancer survivors through earlier recognition and intervention. Although women diagnosed with stages I to III breast cancer have an excellent prognosis with 5-year relative survival >90%, specific adjuvant therapies have been reported to lead to cardiovascular (CV) events that impair health-related quality of life and/or lead to premature CVD death. CV events including acute myocardial infarction, stroke, and venous thromboembolism have been reported to be associated with adjuvant chemotherapy, biological agents, radiation therapy, and/or hormonal therapies. These treatment-related CV events pose a significant public health problem because they will affect the increasing number of breast cancer survivors’ health-related quality of life over a long-life expectancy. Currently, no standard risk model exists to predict the risk of CV events associated with multiple adjuvant breast cancer therapies in the presence of established CV risk factors (such as hypertension, hyperlipidemia, smoking) to inform practice guidelines and promote shared clinical decision-making. Such models can inform women before treatment about the potential risks of CVD from alternative treatment strategies while maintaining the best chances for cancer cure. These models can also help to identify women at highest risk of CVD after therapy who would potentially benefit from earlier and more intensive CV monitoring via routine imaging and/or use of preventive medications to mitigate risk of CV events. To address this gap, our study will create risk prediction models by analyzing a large, demographically heterogeneous cohort of adult women (N=40,500) with newly diagnosed stages I to III invasive breast cancer in real-world health care settings. We will study women diagnosed from 2008-2020 and followed up to 15 years using the comprehensive electronic records of one of the largest health plans in the U.S., Kaiser Permanente. In Aim 1, we will assess incident CV events (acute myocardial infarction, stroke, heart failure) following adjuvant breast cancer therapies, adjusting for tumor characteristics and CVD risk factors such as age, race/ethnicity, pre-existing CVD, CVD medications (statins, anti-hypertensives, anti- diabetics), hypertension, diabetes, BMI, and smoking. We will then estimate whether the risk of CV events is greater in the breast cancer cohort versus an age, race- matched cancer-free cohort. In Aim 2, we will create and validate risk prediction models for early (<1 year) and late (up to 15 years) CV events. Our project will be the first to estimate the association of multiple established CVD risk factors with the risk of breast cancer adjuvant treatment-related CV events in a real-world, ethnically and socioeconomically diverse community-based cohort. Our risk prediction models will provide new information to guide evidence-based clinical decision-making concerning adjuvant therapy use for breast cancer and concurrent and post-treatment cardio-oncology care.

项目摘要在美国300万乳腺癌存活中，近20％患有心血管疾病（CVD）。这国家癌症研究所，NHLBI和专业肿瘤学和心脏病学会都认可了通过早期识别和干预措施减少乳腺癌存活中CVD燃烧的重要性。尽管被诊断为I阶段至III乳腺癌的妇女的预后非常出色，相对5年据报道，生存> 90％，特定的调整疗法会导致损害的心血管（CV）事件与健康有关的生活质量和/或导致过早的CVD死亡。简历活动包括急性心肌据报道，梗塞，中风和静脉血栓症与调整有关化学疗法，生物学剂，放射疗法和/或激素疗法。这些与治疗相关的简历事件构成了一个重大的公共卫生问题，因为它们会影响乳腺癌数量增加幸存者在长寿的预期中与健康相关的生活质量。目前，尚无标准风险模型预测与多种调整乳腺癌疗法相关的简历事件的风险已建立的简历危险因素（例如高血压，高脂血症，吸烟），以告知实践指南并促进共同的临床决策。这样的模型可以在治疗前告知妇女关于替代治疗策略中CVD的潜在风险，同时保持最佳机会癌症治疗。这些模型还可以帮助识别治疗后CVD风险最高的女性通过常规成像和/或预防性使用，可能从早期和更密集的简历监测中受益减轻简历事件风险的药物。为了解决这一差距，我们的研究将通过分析具有新诊断的大型，人口统计学上异质的成年女性（n = 40,500）在现实世界中的医疗保健环境中，I阶段至III侵入性乳腺癌。我们将研究被诊断为诊断的妇女 2008 - 2020年，使用最大健康之一的综合电子记录进行了长达15年的跟进在美国的计划，Kaiser Permanente。在AIM 1中，我们将评估事件CV事件（急性心肌梗塞，中风，心力衰竭）可调节乳腺癌治疗后，调整肿瘤特征和CVD风险诸如年龄，种族/种族，现有CVD，CVD药物（他汀类药物，抗亚型，抗抗菌，抗 - 糖尿病患者），高血压，糖尿病，BMI和吸烟。然后，我们将估计CV事件的风险是否是与乳腺癌队列相比，与种族匹配的无癌队列相比，乳腺癌队列更大。在AIM 2中，我们将创建并验证早期（<1年）和晚期（长达15年）CV事件的风险预测模型。我们的项目将是第一个估算多个已建立的CVD风险因素与乳腺癌风险的关联的关联在现实世界中，以种族和社会经济多样性的社区同类群体中与治疗相关的简历事件。我们的风险预测模型将提供新的信息来指导基于证据的临床决策有关调整乳腺癌以及并发和治疗后心脏肿瘤护理的使用。