Non-invasive evaluation of indeterminate pulmonary nodules

不确定肺结节的无创评估

基本信息

批准号：
9753730
负责人：
PIERRE P. MASSION
金额：
$ 37.61万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-08-03 至 2020-10-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9753730
关键词：
Address Anxiety Autoantibodies Benign Biological Markers Biopsy Blood Cessation of life Characteristics Clinical Clinical Management Clinical Trials Community Hospitals Data Data Set Diagnostic Discrimination Disease Epidemic Evaluation Goals Health Care Costs Healthcare Image Image Analysis Individual Intervention Investigation Knowledge Laboratories Lung Lung nodule Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Modeling Molecular Molecular Profiling Molecular Structure Morbidity - disease rate Nodule Patients Peptides Performance Population Probability Radiation Research Risk Risk Estimate Scanning Structure Techniques Technology Testing Thoracotomy Time Validation X-Ray Computed Tomography automated image analysis base blood-based biomarker candidate marker chest computed tomography cohort computed tomography screening cost diagnostic accuracy follow-up high risk imaging biomarker improved innovation low-dose spiral CT lung cancer screening molecular marker noninvasive diagnosis novel personalized care predictive modeling predictive tools prospective public health relevance quantitative imaging radiomics screening screening program specific biomarkers

项目摘要

DESCRIPTION (provided by applicant): We are facing an epidemic of indeterminate pulmonary nodules (IPNs), not only those found incidentally, but also through the proliferation of CT screening programs targeting high-risk individuals for lung cancer following the encouraging results of the National Lung Screening Trial (NLST). Although the large majority of IPNs are benign, there are currently no effective predictive tools to discriminate benign from malignant nodules, leading to a large number of follow-up CTs, unnecessary invasive biopsies, anxiety, and wasted healthcare spending. Our project addresses this deficiency in knowledge, which we expect will result in improved non-invasive testing and paradigm-shifting prediction models in the clinical management of patients with IPNs. This project has the potential to transform the management of individuals presenting with IPNs. We aim at obtaining significant gains in non-invasive diagnostic accuracy of screening-detected and incidentally-detected IPNs by integrating clinical variables, innovative quantitative structural CT variables with novel blood-based biomarker candidates of IPNs. We will produce actionable diagnostic prediction models to personalize care and identify the small subset of individuals who will need a definitive intervention for lung cancer, and conversely, others who are at very low risk and do not require extensive follow-up. Based on findings from this project, we anticipate 1) using longitudinal data to improve our prediction accuracy for IPNs over time; 2) reduction in the rate of unneeded thoracotomies, the burden of unnecessary follow-up including anxiety; 3) ultimately increase the rate of cure and reduction of unnecessary radiation and healthcare cost.

描述（由申请人提供）：我们面临着不确定性肺结节（IPN）的流行，不仅是那些偶然发现的，而且是在国家癌症中心取得令人鼓舞的结果之后，针对肺癌高危人群的 CT 筛查项目激增所致。肺部筛查试验（NLST）虽然绝大多数IPN是良性的，但目前没有有效的预测工具来区分良性和恶性结节，导致大量的随访。 CT、不必要的侵入性活检、焦虑和浪费的医疗支出。我们的项目解决了这一知识缺陷，我们预计这将改善 IPN 患者的临床管理中的非侵入性检测和范式转变预测模型。我们的目标是通过将临床变量、定量创新结构 CT 变量与新型血液生物标志物候选物相结合，显着提高筛查检测和偶然检测到的 IPN 的无创诊断准确性。的我们将建立可操作的诊断预测模型，以个性化护理并确定需要对肺癌进行明确干预的一小部分人，以及相反，其他风险非常低且不需要广泛随访的人。根据该项目的研究结果，我们预计 1) 使用纵向数据来提高我们对 IPN 的预测准确性；2) 减少不需要的开胸手术的发生率、不必要的随访负担，包括焦虑；3) 最终提高治愈率；和减少不必要的辐射和医疗费用。