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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.

项目概要在美国 300 万乳腺癌幸存者中，近 20% 患有心血管疾病 (CVD)。这美国国家癌症研究所、NHLBI 以及专业肿瘤学和心脏病学会均已认可通过早期识别和干预来减轻乳腺癌幸存者的 CVD 负担的重要性。尽管诊断为 I 至 III 期乳腺癌的女性预后良好，5 年亲属生存率 >90%，据报道，特定辅助治疗会导致心血管 (CV) 事件，从而损害患者的健康健康相关的生活质量和/或导致 CVD 过早死亡。心血管事件，包括急性心肌梗死据报道，梗塞、中风和静脉血栓栓塞与辅助治疗有关化疗、生物制剂、放射疗法和/或激素疗法。这些与治疗相关的简历这些事件会造成重大的公共卫生问题，因为它们会影响不断增加的乳腺癌数量幸存者在漫长的预期寿命期间与健康相关的生活质量。目前，不存在标准的风险模型预测与多种乳腺癌辅助治疗相关的心血管事件风险确定的心血管危险因素（如高血压、高脂血症、吸烟）以指导实践指南并促进共同的临床决策。这种模型可以在治疗前告知女性关于替代治疗策略的 CVD 潜在风险，同时保持最佳机会癌症治愈。这些模型还可以帮助识别治疗后心血管疾病风险最高的女性通过常规成像和/或使用预防性措施进行早期和更密集的 CV 监测可能会受益降低心血管事件风险的药物。为了解决这一差距，我们的研究将通过以下方式创建风险预测模型：分析一大群具有人口统计学异质性的新诊断成年女性 (N=40,500) 现实世界医疗保健环境中的 I 至 III 期浸润性乳腺癌。我们将研究被诊断患有以下疾病的女性 2008 年至 2020 年，并使用最大的健康中心之一的综合电子记录进行了长达 15 年的追踪美国的计划，Kaiser Permanente。在目标 1 中，我们将评估心血管事件事件（急性心肌梗死、乳腺癌辅助治疗后，根据肿瘤特征和 CVD 风险进行调整因素，如年龄、种族/民族、既往患有 CVD、CVD 药物（他汀类药物、抗高血压药物、抗高血压药物）糖尿病患者）、高血压、糖尿病、BMI 和吸烟。然后我们将估计心血管事件的风险是否是与年龄、种族匹配的无癌症队列相比，乳腺癌队列中的这一比例更高。在目标 2 中，我们将创建并验证早期（<1 年）和晚期（长达 15 年）心血管事件的风险预测模型。我们的项目将是第一个评估多个已确定的 CVD 危险因素与乳腺癌佐剂风险之间的关联在现实世界中，种族和社会经济多样化的社区队列中与治疗相关的心血管事件。我们的风险预测模型将提供新信息来指导基于证据的临床决策关于乳腺癌的辅助治疗以及治疗期间和治疗后心脏肿瘤护理。