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)

基本信息

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
项目类别：
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

项目摘要

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方面的最新进展，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，这是全球癌症死亡的主要原因。在美国，指南建议的治疗性治疗后每半年进行一次计算机断层扫描 (CT) 监测，最多持续 5 年，尽管尚不清楚其在降低死亡率方面的益处，但临床试验仍不清楚。在美国 NSCLC 人群中尚未报告 CT 成像监测的情况，这一研究差距令人震惊，预示着临床指南中的证据质量较低。模式和下游结果，这两者都是制定治疗性治疗后监测的循证建议所必需的，该项目“推进不同人群的精准肺癌监测和结果”(PLUS2) 将创建。这一独特的数据源用于研究、了解和优化肺癌监测和下游结果，以 PCORI 和 NCI 资助的 OneFlorida+ 临床研究联盟（社区实践网络）的现有基础设施和肺癌筛查登记处的初步数据为基础。 PLUS2 为佛罗里达州、佐治亚州和阿拉巴马州提供服务，将利用电子健康记录、索赔和系统级因素中的多级数据，了解已完成治疗性治疗的早期 NSCLC 患者（n~27,217； 2012-2022 年（回顾性队列）和 2022-2025 年（前瞻性队列）的中位年龄 70 岁该项目的总体目标是评估肺癌监测策略（主要是半年度与年度 CT 监测）的相对有效性。通过从 NCI 的肺癌干预和治疗中生成以前无法获得的真实世界数据，对美国人群中不同早期 NSCLC 患者的长期结果进行评估。监测建模网络（CISNET）用于经过验证的模拟模型，该提案直接响应了改善肺癌监测候选者以患者为中心的决策的呼吁，对于目前监测的净效益尚不确定的人来说，这项研究是肺癌的基础。监视实践的改变。