Personalized screening for lung cancer: the importance of co-existing chronic conditions to clinical practice and policy

肺癌的个性化筛查：共存慢性病对临床实践和政策的重要性

基本信息

批准号：
10393330
负责人：
Dejana K Braithwaite
金额：
$ 63.75万
依托单位：
UNIVERSITY OF FLORIDA
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：
2020-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10393330
关键词：
Adult Age American Cancer Society Attention Cancer Etiology Cancer Intervention Cancer Intervention and Surveillance Modeling Network Cancer Patient Cessation of life Chronic Chronic Obstructive Airway Disease Clinical Trials Data Decision Making Diagnosis Diagnostic Procedure Disease Early Diagnosis Elderly Electronic Health Record Eligibility Determination Ethnic Origin Funding Geography Goals Health Impairment Infrastructure Intervention Knowledge Life Expectancy Link Lung Malignant neoplasm of lung Modeling Morbidity - disease rate Observational Study Outcome Participant Patients Persons Policies Population Procedures Prospective cohort Provider Public Health Pulmonary Emphysema Race Randomized Clinical Trials Retrospective cohort Risk Risk Factors Smoker Smoking Smoking History Socioeconomic Status Spottings Therapeutic procedure Thoracic Radiography Time Uncertainty Work base cancer surgery clinical practice comorbidity compare effectiveness data standards early screening former smoker high risk improved low dose computed tomography lung cancer screening meetings member models and simulation multiple chronic conditions patient oriented patient population personalized screening public health relevance pulmonary function repository routine screening screening screening guidelines simulation tool

项目摘要

Abstract / summary Lung cancer is the leading cause of cancer death in the US and worldwide, largely because most patients have advanced, incurable disease at the time of diagnosis. However, lung cancer screening (LCS) with low-dose computed tomography (LDCT) has the potential to revolutionize lung cancer outcomes through early detection. As LCS is disseminated into real-world settings and populations, a key outstanding question is whether the benefits/harms ratio found in clinical trials will apply to an older and sicker population. The basic conundrum facing LCS candidates is that the single risk factor most strongly linked to lung cancer -- smoking history -- is also strongly linked to morbidity and death from non-lung cancer causes (e.g. chronic obstructive pulmonary disease emphysema), which limit life expectancy and increase risk of complications from diagnostic or therapeutic procedures. The overarching goal of our proposed study is to precisely characterize this vulnerable subpopulation with high comorbidity burden, quantifying for them the benefits and harms of LCS to enable more informed decision-making by patients contemplating LCS. Our study will help close this knowledge gap by leveraging real-world data to more fully characterize this subpopulation of “marginal” LCS candidates, reducing the uncertainty currently facing patients and providers. More specifically, we propose to leverage electronic health records and claims data for patients ages 55-80 (n~34,039) undergoing annual screening with LDCT in geographically diverse real-world settings from 2016-2022. We will then use these observational data with validated models in the Cancer Intervention Simulation Network to simulate LCS outcomes in the real-world US population. By generating previously unavailable real-world data for use in validated simulation models, this proposal responds directly to calls to improve patient- centered decision-making in LCS candidates for whom the net benefits of screening are currently highly uncertain.

摘要 /摘要肺癌是美国和全球癌症死亡的主要原因，主要是因为大多数患者在诊断时患有可治疗疾病。但是，肺癌低剂量计算机断层扫描（LDCT）的筛查（LCS）有可能革新肺癌结局通过早期检测。由于LCS被传播到现实世界中和人口，关键的关键问题是临床中的收益/危害比率是否试验将适用于年龄较大和病人。面对LCS候选者的基本难题是与肺癌最密切相关的单一危险因素 - 吸烟史 - 也很强烈与非肺癌原因的发病率和死亡有关（例如慢性阻塞性肺疾病肺气肿），限制了预期寿命并增加并发症的风险诊断或治疗程序。我们拟议的研究的总体目标是精确用高的合并症伯恩（Burnen）来表征这种脆弱的亚人群，为他们量化 LCS的益处和伤害使患者打算更明智的决策 LCS。我们的研究将通过利用现实世界的数据更充分地利用现实世界来帮助缩小这一知识差距表征“边际” LCS候选者的亚群，减少了当前的不确定性面对患者和提供者。更具体地说，我们建议利用电子健康记录并索赔55-80岁（n〜34,039）的患者进行LDCT年度筛查的数据 2016 - 2022年从地理上多样化的现实环境。然后，我们将使用这些观测癌症干预模拟网络中具有经过验证模型的数据以模拟LCS 现实世界中的成果。通过生成先前不可用的现实世界数据为了在经过验证的模拟模型中使用，该建议直接响应改善患者的呼吁 - 在LCS候选人中以净筛查的净收益为中心的决策高度不确定。