Achieving appropriate, safe, and patient-centered lung cancer screening

背景：肺癌筛查（LCS）降低了肺癌死亡率，但也可能造成伤害，特别是 当应用于同时存在严重健康问题的患者时。认识到这些权衡，指导方针 建议“有健康问题，大大限制预期寿命或能力， 治疗性肺手术”不应该被筛选，所有考虑LCS的患者都应该接受共享的 决策制定（SDM）过程，与临床医生一起审查LCS的益处和危害。然而这些 这些建议很难实现，因为几乎没有证据可以指导临床医生在哪些健康问题上采取行动。 问题或其他患者因素会使LCS的平衡从净收益变为净伤害，并且对 当预期获益很小时，退伍军人和临床医生需要进行LCS决策。 目的：我们提出了一个顺序解释性混合方法研究，具有以下3个具体目标： 1.确定由于预期寿命有限或LCS危害增加而导致预测LCS益处不大的因素; 2.识别与现实世界临床医生和退伍军人LCS决策相关的临床患者因素;以及 3.当预测的LCS效益很小时，确定决策方法和决策需求。 方法：Aim 1a.为了确定竞争性（非肺癌）死亡原因何时限制LCS获益，我们将 在符合LCS条件但未经筛选的退伍军人中进行生存分析，建立竞争风险模型 以及应用递归划分来识别临床上有意义的风险组。目标1b。我们将建立一个模型， 确定预测LCS检测的侵入性手术并发症的患者因素组合 调查结果。目标2：我们将比较与实际LCS决策相关的因素与 使用来自10个VA研究中心的数据预测LCS获益甚微（Aim 1模型），这些研究中心跟踪了符合LCS条件的患者 退伍军人被认为“病得太重”，无法接受LCS，他们获得了LCS，并接受了LCS。我们将建立混合效果 逻辑回归模型来完成这些子目标：2a-识别与临床医生相关的患者因素 认为退伍军人“不适合”LCS，描述提供LCS的各研究中心的差异，以及是否 弱势群体（少数民族、农村、无家可归者）被不成比例地认为“不适合”地方社区服务。2b- 确定与退伍军人决定拒绝与接受LCS相关的临床和人口统计学因素。目标3： 我们将采访多达30名临床医生和30名退伍军人（15人接受LCS，15人拒绝LCS）， 根据我们的目标1模型，预测的LCS效益是微不足道的。对于临床医生，我们将探索信念， LCS决策的预期结果和现场层面的影响，介绍小插曲，以了解如何 提供预测的LCS效益（目标1模型）影响LCS决策。对于患者，我们将探索 LCS讨论的经验，与LCS相关的卫生优先事项，以及对决策的其他影响。 对于所有参与者，我们将评估信息需求和偏好，以在护理点支持SDM。 对退伍军人医疗保健的预期影响：最大限度地发挥LCS的救生潜力， 额外的伤害和浪费VA资源，必须适当应用LCS。这项提案将奠定 为个性化决策工具的未来开发、测试和实施提供基础信息， 优化LCS的患者选择，并在护理点促进退伍军人和VA临床医生之间的SDM。 这项工作对于实现安全，适当和以退伍军人为中心的护理至关重要，因为肺癌筛查是 在整个弗吉尼亚州实施-我们在国家健康促进和疾病中心的合作伙伴的优先事项 预防、初级保健办公室和国家肺医学项目办公室。这项工作 解决了舒尔金部长的优先事项，即有效地将资源集中在退伍军人的高影响问题上。

Background: Lung cancer screening (LCS) reduces lung cancer death, but can also cause harm, especially when applied to patients with co-existing serious health problems. Recognizing these trade-offs, guidelines recommend that persons with “a health problem that substantially limits life expectancy or ability to have curative lung surgery” should not be screened, and that all patients considering LCS should undergo a shared decision-making (SDM) process to review LCS benefits and harms with their clinicians. Yet these recommendations are difficult to achieve, as there is little evidence to guide clinicians on which health problems or other patient factors tip the balance of LCS from net benefit to net harm, and little is known about Veteran and clinician approaches to and needs for LCS decision-making when anticipated benefit is marginal. Objectives: We propose a sequential explanatory mixed methods study with the following 3 specific aims: 1. Identify factors that predict little LCS benefit due to limited life expectancy or increased LCS harms; 2. Identify clinical patient factors associated with real-world clinician and Veteran LCS decisions; and 3. Characterize approaches to and needs for decision-making when predicted LCS benefit is marginal. Methods: Aim 1a. To determine when competing (non-lung cancer) causes of death limit LCS benefit, we will conduct a survival analysis among LCS-eligible but unscreened Veterans, building a competing risks model and applying recursive partitioning to identify clinically meaningful risk groups. Aim 1b. We will build a model to identify combinations of patient factors that predict complications of invasive procedures for LCS-detected findings. Aim 2: We will compare how well factors associated with actual LCS decisions align with factors that predict little LCS benefit (Aim 1 models), using data from 10 VA sites that tracked rates at which LCS-eligible Veterans were deemed “too sick” for LCS, were offered LCS, and accepted LCS. We will build mixed effects logistic regression models to complete these subaims: 2a-Identify patient factors associated with clinicians deeming Veterans “not appropriate” for LCS, characterizing variation across sites in offering LCS, and whether vulnerable groups (minorities, rural, homeless) are disproportionately deemed “not appropriate” for LCS. 2b- Identify clinical and demographic factors associated with Veteran decisions to decline vs accept LCS. Aim 3: We will interview up to 30 clinicians and 30 Veterans (15 who accepted, 15 who declined LCS) for whom predicted LCS benefit is marginal based on our Aim 1 models. For clinicians, we will explore beliefs about, expected outcomes of, and site-level influences on LCS decision-making, presenting vignettes to learn how providing predicted LCS benefit (Aim 1 models) affects LCS decision-making. For patients, we will explore experiences with LCS discussions, health priorities relative to LCS, and other influences on decision-making. For all participants, we will assess informational needs and preferences to support SDM at the point of care. Anticipated Impacts on Veteran's Healthcare: To maximize the life-saving potential of LCS without creating additional harms and wasting VA resources, LCS must be applied appropriately. This proposal will lay the groundwork to inform future development, testing, and implementation of a personalized decision tool to optimize patient selection for LCS and facilitate SDM between Veterans and VA clinicians at the point of care. This work is essential to achieve safe, appropriate, and Veteran-centered care as lung cancer screening is implemented across VA – a priority for our partners in the National Center for Health Promotion & Disease Prevention, the Office of Primary Care, and the National Program Office for Pulmonary Medicine. This work addresses Secretary Shulkin’s priority to focus resources efficiently on high-impact problems for Veterans.