Optimizing Lung Cancer Screening in Cancer Survivors

优化癌症幸存者的肺癌筛查

• 批准号: 10317359
• 负责人: Chung Yin Kong
• 金额: $ 71.88万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10317359
• 关键词: Age; Biochemical; Breast; Cancer Etiology; Cancer Model; Cancer Survivor; Clinical Trials; Colorectal; Colorectal Cancer; Data; Decision Making; Detection; Development; Diagnosis; Disease; Eligibility Determination; Female; Frequencies; General Population; Goals; Health Care Costs; Malignant Neoplasms; Malignant neoplasm of lung; Methods; Modeling; Outcome; Patient-Focused Outcomes; Patients; Population; Population Heterogeneity; Preventive service; Prostate; Quality of life; Radiation therapy; Recording of previous events; Recurrence; Regimen; Risk; Screening Result; Screening for cancer; Second Primary Cancers; Smoking; Smoking History; Survivors; Time; Tobacco use; Treatment Side Effects; United States; Woman; base; cancer diagnosis; cohort; colorectal cancer screening; comorbidity; cost effectiveness; effectiveness evaluation; ethnic diversity; high risk; innovation; lung cancer screening; men; models and simulation; mortality; mortality risk; multi-ethnic; multi-racial; novel; population based; racial and ethnic; racial diversity; randomized trial; screening; screening guidelines; sex; survivorship; tobacco exposure

The goal of the proposal is to identify optimal lung cancer (LC) screening strategies for breast (BC), prostate (PC), colorectal (CRC) cancer survivors. We will accomplish these goals by developing and validating a novel Multi-Racial and Ethnic Lung Cancer Model (MELCAM) that will simulate LC development, progression, screening, treatment, and survival in a multiethnic cancer survivor population. We will then assess the effectiveness and cost-effectiveness (CE) of different LC screening strategies for these survivors. All together, there are >6 million BC, CRC and PC survivors in the US, and as these cancers tend to be diagnosed in early stage, many survivors live for a long time and develop and may die from second cancers. Cancer survivors are also at increased risk of developing LC due to relatively high rates of smoking (up to 50-60%), age, and treatment-related side effects. As a result, >15% of LC are diagnosed in cancer survivors, and LC is the top cause of cancer-related mortality in this population. Little is known about optimal LC screening for cancer survivors who have been excluded from prior randomized trials (RCT) and have a different harm/benefit ratio from screening due to competing risk of death from their first cancer and higher burden of comorbidities. Lack of data to guide decisions about LC screening in cancer survivors has profound negative impact on survivorship, including under and overuse of LC screening, resulting in worse outcomes and increased healthcare costs. It is unlikely that RCT assessing the benefits of LC screening for cancer survivors will ever be conducted. Thus, there is an urgent need to use alternative methods to determine the optimal screening strategy for these patients. In this study, we propose using simulation modeling, an approach complementary to RCTs, to assess the harms and benefits of LC screening in cancer survivors. The Specific Aims are to: (1) Derive and validate a model (MELCAM), based on a well-established framework, to simulate LC screening in BC, PC and CRC cancer survivors from diverse racial and ethnic backgrounds; (2) Determine the most effective and CE strategies for LC screening in BC survivors; (3) Identify the optimal LC screening strategies in PC survivors and determine their CE; and (4) Evaluate the effectiveness and CE of LC screening for CRC survivors. To achieve these Aims, we will use data from several large, representative, population-based cancer cohorts and robust harmonization methods to develop, calibrate, and validate MELCAM by incorporating the development, screening, work-up, treatment and survival of LC in multiethnic survivors of BC, PC and CRC (Aim 1). We will then use the model to simulate RCTs evaluating the effectiveness (in terms of maximizing survival, quality of life, and other patient-centered outcomes) and CE of LC screening regimens (eligibility, frequency and duration) in these cancer survivors (Aims 2-4). The study will be innovative in applying state-of- the-art modeling approaches to evaluate LC screening in a diverse population of cancer survivors, and results will have direct implications for the management of a large group of survivors.

该提案的目的是确定乳腺癌（BC），前列腺的最佳肺癌（LC）筛查策略 （PC），结直肠（CRC）癌症幸存者。我们将通过制定和验证小说来实现这些目标 多种族和民族肺癌模型（MELCAM）将模拟LC的发展，进展， 多种族癌症幸存者人群的筛查，治疗和生存。然后，我们将评估 这些幸存者的不同LC筛查策略的有效性和成本效益（CE）。一起， 美国有600万，CRC和PC幸存者，因为这些癌症往往会在早期被诊断出 舞台上，许多幸存者长期生活，发展并可能死于第二癌。癌症幸存者是 同样，由于吸烟率相对较高（高达50-60％），年龄和 与治疗相关的副作用。结果，在癌症幸存者中诊断出> 15％的LC，LC是最高的 该人群中与癌症相关的死亡率的原因。关于癌症的最佳LC筛查知之甚少 从先前的随机试验（RCT）中排除并具有不同的危害/福利比的幸存者 筛查因其第一次癌症的死亡风险和合并症负担较高而引起的死亡风险。缺少 指导有关癌症幸存者LC筛查决策的数据对 生存期，包括LC筛查的不足和过度使用，导致结果较差并增加 医疗保健费用。 RCT不太可能评估LC筛查对癌症幸存者的好处 实施。因此，迫切需要使用替代方法来确定最佳筛选 这些患者的策略。在这项研究中，我们建议使用模拟建模，一种方法互补 为了评估癌症幸存者LC筛查的危害和益处。具体目的是：（1） 基于建立良好的框架来得出和验证模型（MELCAM），以模拟LC筛选 来自不同种族和种族背景的BC，PC和CRC癌症幸存者； （2）确定最多 卑诗省幸存者的LC筛查的有效和CE策略； （3）确定最佳的LC筛选策略 PC幸存者并确定其CE； （4）评估CRC的LC筛选的有效性和CE 幸存者。为了实现这些目标，我们将使用来自几个大型，代表性的，基于人群的癌症的数据 通过合并来开发，校准和验证MELCAM的队列和强大的协调方法 BC，PC和CRC多种族幸存者中LC的开发，筛查，工作，治疗和存活 （目标1）。然后，我们将使用该模型模拟评估有效性的RCT（就最大化而言 LC筛查方案的生存，生活质量和其他以患者为中心的结果）（资格，资格 这些癌症幸存者中的频率和持续时间）（目标2-4）。该研究将在应用最新 ART建模方法评估癌症幸存者种群中LC筛查的方法，并结果 将直接对一大批幸存者的管理产生影响。