Advancing Precision Lung Cancer Surveillance and Outcomes in Diverse Populations (PLuS2)

推进不同人群的精准肺癌监测和结果 (PLuS2)

• 批准号: 10752848
• 负责人: Jiang Bian
• 金额: $ 55.65万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-05 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10752848
• 关键词: Adopted; Age; Alabama; American Society of Clinical Oncology; Body Weight decreased; Cancer Etiology; Cancer Intervention and Surveillance Modeling Network; Cancer Patient; Catalogs; Cessation of life; Characteristics; Chest Pain; Clinical; Clinical Research; Clinical Trials; Collaborations; Community Networks; Community Practice; Community of Practice; Coughing; Data; Data Sources; Decision Analysis; Decision Making; Detection; Diagnostic Imaging; Electronic Health Record; Ethnic Origin; European; Excision; Florida; Funding; Future; Geography; Goals; Guidelines; Image; Infrastructure; Knowledge; Lead; Malignant Neoplasms; Malignant neoplasm of lung; Modeling; Natural Language Processing; Non-Small-Cell Lung Carcinoma; Operative Surgical Procedures; Outcome; Patients; Pattern; Policies; Population; Population Heterogeneity; Prognosis; Prospective cohort; Public Health; Race; Radiology Specialty; Recommendation; Recurrence; Registries; Reporting; Research; Retrospective cohort; Scanning; Shortness of Breath; Smoking Status; Socioeconomic Status; Survival Rate; Symptoms; System; Thoracic Radiography; X-Ray Computed Tomography; black patient; clinical trial enrollment; comorbidity; comparative effectiveness; compare effectiveness; data integration; electronic health data; electronic structure; evidence based guidelines; improved; innovation; lung cancer screening; models and simulation; mortality; multimodality; participant enrollment; patient oriented; patient population; pulmonary function; randomized, clinical trials; repository; rurality; screening; social health determinants; sociodemographics; socioeconomics; study population; surveillance data; surveillance imaging; surveillance strategy; unstructured data; uptake

Due in part to recent advances in screening and treatment, the 5-year relative survival rate for patients with early-stage non-small cell lung cancer (NSCLC), the leading cause of cancer death worldwide, continues to increase each year. The uptake of guideline-recommended computed tomography (CT) imaging surveillance semiannually for 2 years and annually for up to 5 years following curative-intent therapy is increasing rapidly in the U.S., despite unclear evidence regarding its benefit in reducing mortality. Furthermore, clinical trials of CT imaging surveillance have not been reported among U.S. populations with NSCLC. This gap in research is alarming and portends a low quality of evidence in clinical guidelines. Currently, no comprehensive lung cancer surveillance data source exists that catalogs real-world lung cancer surveillance utilization patterns and downstream outcomes, both of which are necessary to develop evidence-based recommendations for surveillance following curative-intent therapy. This project, Advancing Precision Lung Cancer Surveillance and Outcomes in Diverse Populations (PLUS2), will create this unique data source to study, understand, and optimize lung cancer surveillance and downstream outcomes. Building on the extant infrastructure and preliminary data from the lung cancer screening registry of the PCORI- and NCI-funded OneFlorida+ Clinical Research Consortium, a network of community practices that serve Florida, Georgia, and Alabama, PLUS2 will leverage multilevel data from electronic health records, claims, and system-level factors for patients with early-stage NSCLC who have completed curative-intent therapy (n~27,217; median age 70) from 2012-2022 (retrospective cohort) and 2022-2025 (prospective cohort). The overarching goal of the project is to evaluate the comparative effectiveness of lung cancer surveillance strategies, principally semi-annual versus annual CT surveillance, in relation to long-term outcomes among diverse patients with early-stage NSCLC within the U.S. population. By generating previously unavailable real-world data from NCI’s Lung Cancer Intervention and Surveillance Modeling Network (CISNET) for use in validated simulation models, this proposal responds directly to calls to improve patient-centered decision-making in lung cancer surveillance candidates for whom the net benefits of surveillance are currently uncertain. This study is foundational for lung cancer surveillance practice change.

部分由于筛查和治疗的最新进展，早期非小细胞肺癌（NSCLC）患者的5年相对生存率每年持续增加，NSCLC是全球癌症死亡的主要原因。在美国，指南推荐的计算机断层扫描（CT）成像监测在治疗目的治疗后每半年持续2年和每年持续长达5年的使用正在迅速增加，尽管关于其在降低死亡率方面的益处的证据尚不清楚。此外，在美国NSCLC人群中尚未报告CT成像监测的临床试验。研究中的这一差距令人担忧，并预示着临床指南中的证据质量较低。目前，没有全面的肺癌监测数据源存在，目录真实世界的肺癌监测利用模式和下游结果，这两者都是必要的，以制定循证建议监测后的治疗意图的治疗。该项目名为“在不同人群中推进精确肺癌监测和结果”（PLUS 2），将创建这种独特的数据源，以研究、理解和优化肺癌监测和下游结果。PLUS 2建立在现有基础设施和来自PCRI和NCI资助的One佛罗里达+临床研究联盟（一个服务于佛罗里达、格鲁吉亚和亚拉巴马的社区实践网络）肺癌筛查登记处的初步数据基础上，将利用来自已完成治愈性治疗的早期NSCLC患者的电子健康记录、索赔和系统级因素的多层次数据2012-2022年（回顾性队列）和2022-2025年（前瞻性队列）（n~ 27，217;中位年龄70岁）。该项目的总体目标是评估肺癌监测策略的比较有效性，主要是半年与每年CT监测，与美国人群中不同早期NSCLC患者的长期结局有关。通过从NCI的肺癌干预和监测建模网络（CISNET）中生成以前不可用的真实世界数据，用于验证的模拟模型，该提案直接响应呼吁，以改善以患者为中心的肺癌监测候选人的决策，对他们来说，监测的净效益目前还不确定。这项研究是肺癌监测实践改变的基础。