Modeling Best Approaches for Cardiovascular Disease Prevention in Cancer Survivors

模拟癌症幸存者心血管疾病预防的最佳方法

• 批准号: 10608446
• 负责人: Chung Yin Kong
• 金额: $ 71.3万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10608446
• 关键词: Affect; Aspirin; Atherosclerosis; Attenuated; Biochemical; Breast; Calcium; Calibration; Cancer Model; Cancer Survivor; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Cessation of life; Clinical Trials; Cost Effectiveness Analysis; Data; Decision Making; Development; Disease Outcome; General Population; Genetic; Genetic Risk; Goals; Guidelines; High Prevalence; Hyperlipidemia; Hypertension; Incidence; Life; Lipids; Lung; Malignant Neoplasms; Methods; Modeling; Morbidity - disease rate; Natural History; Outcome; Patients; Population; Population Heterogeneity; Populations at Risk; Prevention strategy; Preventive care; Primary Prevention; Prostate; Quality of life; Quality-Adjusted Life Years; Radiation therapy; Randomized, Controlled Trials; Recommendation; Recurrence; Recurrent Malignant Neoplasm; Regional Disease; Risk; Risk Factors; Risk Reduction; Source; Stratification; Survivors; Testing; Treatment-Related Cancer; United States; Woman; cancer recurrence; cancer risk; cancer therapy; cardiovascular disorder prevention; cardiovascular disorder risk; chemotherapy; chest computed tomography; cohort; comorbidity; comparative effectiveness; computed tomography screening; coronary calcium scoring; cost effectiveness; data harmonization; effectiveness evaluation; ethnic minority; genetic risk factor; improved; in silico; innovation; low dose computed tomography; men; models and simulation; mortality; multi-ethnic; novel; polygenic risk score; population based; racial minority; sex; simulation; targeted treatment

PROJECT SUMMARY The overall goal of this proposal is to identify optimal strategies for primary prevention of cardiovascular disease (CVD) for survivors of breast (BC), prostate (PC) and lung (LC) cancer. All together, there are >6 million BC, PC and LC survivors in the US. While cancer is a major source of morbidity and mortality, the majority of BC and PC as well as many early-stage LC survivors die of comorbidities, particularly CVD. Cancer survivors have increased rates of both CVD risk factors as well as CVD itself, and CVD is the leading cause of death among BC and PC survivors. Among LC survivors, CVD-related deaths account for ~30% of mortality; this proportion is higher among the growing number identified with early-stage LC. In the general population, primary prevention with lipid-lowering agents (i.e., statins) and aspirin is highly effective for decreasing CVD incidence and mortality, but these guidelines for primary CVD prevention cannot be extrapolated to cancer survivors. Approaches for CVD prevention in cancer survivors need to consider traditional risk factors (including genetic risks) for CVD as well as CVD risk from certain cancer treatments. Additionally, competing risks from cancer recurrence or comorbidities may limit the long-term benefits of primary CVD prevention. Finally, the cancer itself, cancer treatment-related complications, and a higher prevalence of comorbidities can negatively impact quality-of-life and attenuate the absolute improvement in quality-adjusted life expectancy and the cost effectiveness (CE) of primary CVD prevention. Lack of specific data applicable to cancer survivors has profound negative impact, resulting in worse cardiovascular outcomes. It is unlikely that randomized controlled trials (RCT) assessing the benefits of CVD preventive strategies for cancer survivors will be ever conducted. Thus, there is an urgent need to use alternative methods to optimize preventive care recommendations for this growing population. We propose using simulation modeling, an approach complementary to clinical trials, to assess the harms, benefits, and CE of CVD prevention in diverse populations of cancer survivors. The Specific Aims are to: (1) Develop an Integrated Multi-Ethnic Cancer model (IMEC) to incorporate the development, progression, and outcomes of CVD among a diverse population of BC, PC and LC survivors; (2) Identify BC survivors who will benefit from and determine the CE of primary CVD prevention; (3) Determine effectiveness and CE of primary CVD prevention in PC survivors; and (4) Determine the most effective and CE CVD prevention strategies for LC survivors. To achieve these Aims, we will use data from several large, diverse and nationally representative, population-based cancer and cardiovascular cohorts to create, calibrate, and validate IMEC (Aim 1). Then, we will use the model to test our hypothesis by conducting in-silico RCTs (Aims 2-4). Our study is innovative in using state-of-the-art modeling methods and novel data harmonization, statistical and simulation approaches to optimize the use of CVD preventive strategies in cancer survivors. The results will have direct implications for the management of large numbers of survivors and guide patient decision-making.

项目摘要 该提案的总体目标是确定主要预防心血管的最佳策略 乳房幸存者（BC），前列腺（PC）和肺癌（LC）癌症的疾病（CVD）。一起，有> 6 公元前百万，美国PC和LC幸存者。癌症是发病率和死亡率的主要来源，但 BC和PC的大多数以及许多早期LC幸存者都死于合并症，尤其是CVD。癌症 幸存者的CVD风险因素和CVD本身的率都提高，CVD是 卑诗省和PC幸存者之间的死亡。在LC幸存者中，与CVD相关的死亡约占死亡率的30％； 在早期LC确定的增长数量中，这一比例较高。在一般人口中， 降低脂质剂（即汀类药物）和阿司匹林的一级预防对于减少CVD非常有效 发病率和死亡率，但这些预防原发性CVD的指南不能推断为癌症 幸存者。癌症幸存者预防CVD的方法需要考虑传统的风险因素 （包括遗传风险）CVD以及某些癌症治疗的CVD风险。另外，竞争 癌症复发或合并症的风险可能会限制预防原发性CVD的长期收益。 最后，癌症本身，与癌症治疗有关的并发症以及合并症的较高患病率可以 对生活质量产生负面影响，并减轻质量调整的预期寿命和 预防初级CVD的成本效益（CE）。缺乏适用于癌症幸存者的特定数据 深刻的负面影响，导致心血管结局较差。不太可能随机控制 评估CVD预防策略对癌症幸存者的好处的试验（RCT）将永远进行。 因此，迫切需要使用替代方法来优化预防性护理建议 人口增长。我们建议使用模拟建模，一种补充临床试验的方法， 评估癌症幸存者种群中CVD预防的危害，利益和CE。具体 目的是：（1）开发一种综合的多种族癌症模型（IMEC），以结合发展， 卑诗省，PC和LC幸存者的进展和CVD的结果； （2）识别BC 将受益并确定预防初级CVD的CE的幸存者； （3）确定有效性 和PC幸存者预防原发性CVD的CE； （4）确定最有效和CE CVD LC幸存者的预防策略。为了实现这些目标，我们将使用来自几个大型，多样化和的数据 全国代表性的，基于人群的癌症和心血管群，以创建，校准和验证 IMEC（目标1）。然后，我们将使用该模型通过进行内部RCT来检验我们的假设（AIMS 2-4）。我们的 研究使用最先进的建模方法和新的数据协调，统计和 在癌症幸存者中优化使用CVD预防策略的模拟方法。结果将 对管理大量幸存者的管理有直接影响，并指导患者决策。