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

摘要/概要 肺癌是美国和世界范围内癌症死亡的主要原因，主要是因为大多数人都患有肺癌。 患者在诊断时患有晚期不治之症。然而，肺癌 低剂量计算机断层扫描（LDCT）筛查（LCS）有可能彻底改变 肺癌的早期诊断随着LCS被传播到现实世界的环境中， 和人群，一个关键的悬而未决的问题是，临床研究中发现的受益/损害比是否 试验将适用于年龄较大和病情较重的人群。LCS候选人面临的基本难题是 与肺癌最密切相关的单一风险因素-吸烟史-也与肺癌密切相关。 与非肺癌原因（如慢性阻塞性肺疾病）的发病率和死亡率相关 疾病肺气肿），这限制了预期寿命，并增加了并发症的风险， 诊断或治疗程序。我们所提出的研究的首要目标是， 描述这一具有高并发症负担的脆弱亚群的特征，为他们量化 LCS的益处和危害，使患者能够做出更明智的决策， LCS。我们的研究将有助于通过利用真实世界的数据更充分地 描述这个“边缘”LCS候选人的亚群，减少目前的不确定性， 面对患者和供应商。更具体地说，我们建议利用电子健康记录 年龄在55-80岁（n~ 34，039）的患者接受LDCT年度筛查的索赔数据， 2016-2022年地理上多样化的现实世界环境。然后我们将使用这些观察 在癌症干预模拟网络中使用经过验证的模型来模拟LCS 在现实世界中，美国人口。通过生成以前不可用的真实世界数据 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要求， 集中决策的LCS候选人的净效益筛选是目前 非常不确定。

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.