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的最新进展，早期非小细胞肺癌（NSCLC）患者的5年相对存活率是全球癌症死亡的主要原因，每年都在增加。在治疗疗法治疗后每年一次，每年每年多长达5年的指南征用计算机层析成像（CT）成像监视的吸收迅速增加，尽管证据不清楚其在降低死亡率方面的好处。此外，在NSCLC的美国人群中，尚未报告CT成像监视的临床试验。研究差距令人震惊，并预示着临床指南中的证据质量较低。目前，尚无全面的肺癌监测数据，即现实世界中的肺癌监测利用模式和下游结果对现实世界的肺癌监测模式进行了分类，这两种结果对于在治疗治疗后开发了基于证据的建议，这都是必要的。该项目推进了多种人群中的精密肺癌监测和结果，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。建立在PCORI-和NCI资助的Oneflorida+临床研究联盟的肺癌筛查注册表的广泛基础架构和初步数据的基础上，这是一个为佛罗里达州，佐治亚州和阿拉巴马州提供服务的社区实践网络，Plus2将从电子健康记录，策略和系统的策略中授予多级数据，并将其策划的患者用于策略，并策划了策略的患者。（n〜27,217;中位年龄70）2012 - 2022年（回顾性队列）和2022-2025（前瞻性队列）。该项目的总体目标是评估肺癌监测策略的比较有效性，即主要是半年度与年度CT监视，这与美国人群早期NSCLC的长期结局有关。通过从NCI的肺癌干预和监视建模网络（CISNET）中生成以前无法获得的现实世界数据，用于验证的模拟模型中，该提案直接响应以改善以患者为中心的肺癌监测候选者中以患者为中心的决策的呼吁，目前尚不确定监测的净收益。这项研究是肺癌监测实践改变的基础。