PAtient-centered mUltidiSciplinary care for vEterans undergoing surgery (PAUSE): a hybrid 1 clinical effectiveness-implementation intervention trial

为接受手术的退伍军人提供以患者为中心的多学科护理（PAUSE）：一项混合 1 临床有效性实施干预试验

• 批准号: 10675316
• 负责人: Shipra Arya
• 金额: --
• 依托单位: VETERANS ADMIN PALO ALTO HEALTH CARE SYS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10675316
• 关键词: Acceleration; Address; Adherence; Adopted; African American population; Area; Assessment tool; Award; Biopsy; Calibration; Cancer Patient; Cancer Survivor; Cancer Survivorship; Caring; Cessation of life; Clinic; Clinical; Clinical effectiveness; Computerized Medical Record; Consolidated Framework for Implementation Research; Data; Databases; Decision Making; Development; Diagnosis; Disparity; Early Diagnosis; Early identification; Equity; Foundations; Future; Goals; Harm Reduction; Health; Health Care Costs; Health Services; Health Services Research; Histology; Hybrids; Individual; Institution; Intervention; Intervention Trial; Interview; K-Series Research Career Programs; Longevity; Malignant neoplasm of lung; Mentors; Mentorship; Methods; Mission; Modeling; Oncology; Operative Surgical Procedures; Outcome; Outcomes Research; Parents; Patients; Performance; Pilot Projects; Population; Positioning Attribute; Predictive Cancer Model; Program Description; Provider; Qualitative Methods; Radiation exposure; Recurrence; Research; Research Personnel; Risk; Risk Assessment; Screening for cancer; Second Primary Cancers; Services; Site; Smoking History; Structure; Survivors; Thoracic Oncology; Training; Training Programs; Translating; United States Department of Veterans Affairs; Update; Veterans; Veterans Health Administration; Work; acceptability and feasibility; advanced analytics; cancer risk; cancer therapy; career; clinical care; clinical decision support; clinical practice; cohort; demographics; disparity reduction; evidence base; experience; frailty; high risk; implementation intervention; implementation science; implementation strategy; improved; innovation; lung cancer screening; military veteran; mortality; mortality risk; multidisciplinary; novel strategies; oncology program; patient oriented; patient population; precision oncology; predictive modeling; prevent; research and development; risk prediction model; risk stratification; screening; screening program; standard of care; success; support tools; survivorship; tool; uptake

The long-term goal of this project is to improve Veteran health and longevity by developing and implementing an evidence-based screening strategy to prevent death from second primary lung cancer (SPLC) in lung cancer survivors. This is important because SPLC is distinct from recurrence and is one of the main mortality risks for survivors. Despite its importance, there is no evidence-based standard-of-care for basic questions like which patients to screen for SPLC and for how long. As treatment and screening improve and the number of lung cancer survivors increase, there is a critical need for research into interventions to implement evidence-based cancer screening for cancer survivors. To address this need, we propose to adopt an evidence- based strategy increasingly used in initial primary lung cancer (IPLC) screening, risk stratification. Risk stratification has led to marked improvements in IPLC screening, increasing screening efficiency while also containing ballooning healthcare costs and reducing disparities. To achieve similar improvements for SPLC, our group has developed and validated a predictive model to stratify lung cancer survivors by risk of SPLC, now to be piloted in a clinical setting in this project. Our project is innovative as it is the first (to our knowledge) to implement risk stratification for SPLC. The objective of our proposal is to develop a Veteran-specific and disparity-sensitive clinical decision support tool to stratify Veterans by SPLC risk in clinic. Our central hypotheses are that 1) our model can accurately identify Veterans at high risk for SPLC and 2) identification of high-risk patients is feasible in a VA clinical setting. To accomplish the study objective, the following specific aims will be pursued. Aim 1 will validate and adapt our previously developed SPLC risk prediction model for Veterans, utilizing patient demographics, smoking history, and IPLC treatment, stage and histology derived from the VA EMR. Aim 2 will identify factors that influence feasibility and acceptability of a SPLC risk stratification tool, using a mixed methods approach to focus on provider decision-making and structural or systemic influences at the facility level. Aim 3 will translate the SPLC risk prediction model into a clinical decision support tool and pilot the tool at a single VA site, using iterative cycles to improve tool uptake. Following successful completion of this proposal, the expected research outcomes are to have 1) an updated optimal SPLC risk prediction model for Veterans and 2) a feasible clinical decision support tool based on the model, which a clinician can use to identify patients at high risk of SPLC. In addition, the mentored training program described in this proposal will accelerate Dr. Julie Wu’s development into an independent health services researcher. Her mentorship team includes Drs. Arya, Backhus, and Han- leaders in implementation science, thoracic oncology, and predictive modeling. From this proposal, the expected training outcomes will be 1) training in advanced modeling and database analytics and 2) training in qualitative methods and implementation science, which will help the PI achieve her research career goal of bridging the implementation gap between evidence and practice. Moreover, by completing this project, Dr. Wu will establish the training foundation and preliminary data for a CDA-2 application to identify current barriers to screening in high-risk Veteran lung cancer survivors and pilot an intervention aimed at overcoming those barriers. This project will have impact as Dr. Wu is part of the VA National Oncology Program and thus uniquely positioned to guide future expansion of the SPLC screening program across the national VA network.

该项目的长期目标是通过开发和 实施循证筛查策略以预防第二原发肺死亡 肺癌幸存者中的SPLC。这一点很重要，因为SPLC不同于 复发，是幸存者的主要死亡风险之一。尽管它的重要性， 没有基于证据的标准治疗的基本问题，如哪些患者筛选SPLC 以及多久随着治疗和筛查的改善， 增加，迫切需要对干预措施进行研究，以实施基于证据的 癌症幸存者的癌症筛查。为了满足这一需求，我们建议采用一种证据- 基于策略越来越多地用于初始原发性肺癌（IPLC）筛查，风险 分层风险分层导致IPLC筛查的显著改善， 筛查效率，同时还控制不断膨胀的医疗成本并减少差异。 为了实现SPLC的类似改进，我们的团队开发并验证了一种预测性的 根据SPLC风险对肺癌幸存者进行分层的模型，现在将在临床环境中进行试点， 这个项目我们的项目是创新的，因为它是第一个（据我们所知）实施风险 SPLC的分层。我们建议的目标是制定一个专门针对退伍军人和 敏感的临床决策支持工具，用于根据临床SPLC风险对退伍军人进行分层。我们 中心假设是：1）我们的模型可以准确地识别SPLC高风险的退伍军人 和2）在VA临床环境中识别高风险患者是可行的。完成 研究目的，将追求以下具体目标。目标1将验证和调整我们的 先前开发的退伍军人SPLC风险预测模型，利用患者人口统计学， 吸烟史、IPLC治疗、来自VA EMR的分期和组织学。目标2将 确定影响SPLC风险分层工具可行性和可接受性的因素，使用 一种混合方法，侧重于供应商决策和结构或系统 在设施层面的影响。目标3将SPLC风险预测模型转化为临床 决策支持工具，并在单个VA站点试用该工具，使用迭代周期改进工具 摄取。在成功完成这项建议后，预期的研究成果如下 有1）更新的最佳SPLC风险预测模型退伍军人和2）可行的临床 基于该模型的决策支持工具，临床医生可以使用该工具来识别处于高风险状态的患者。 SPLC的风险此外，本建议书中所述的辅导培训计划将 加速Julie Wu博士发展成为独立的卫生服务研究员。她 导师团队包括Arya博士，Backhus和Han-实施科学的领导者， 胸部肿瘤学和预测建模。根据这一建议，预期的培训成果 将是1）高级建模和数据库分析培训，2）定性 方法和实施科学，这将有助于PI实现她的研究生涯目标， 弥合证据与实践之间的执行差距。此外，通过完成这一 吴博士将为CDA-2建立培训基础和初步数据 应用于确定高风险退伍军人肺癌幸存者筛查的当前障碍 并进行旨在克服这些障碍的干预。该项目将产生影响， 博士吴是VA国家肿瘤学计划的一部分，因此具有独特的定位， 未来在全国VA网络中扩大SPLC筛查计划。

项目成果

Optimizing Lung Cancer Screening With Risk Prediction: Current Challenges and the Emerging Role of Biomarkers.

通过风险预测优化肺癌筛查：当前的挑战和生物标志物的新兴作用。

• DOI: 10.1200/jco.23.01060
• 发表时间: 2023
• 期刊: Journal of clinical oncology : official journal of the American Society of Clinical Oncology
• 作者: Wu,JulieTsu-Yu;Wakelee,HeatherA;Han,SummerS
• 通讯作者: Han,SummerS