Department of Thoracic Surgery, Rush University Medical Center, Chicago, Illinois 60612, USA.
J Thorac Oncol. 2013 Jan;8(1):31-6. doi: 10.1097/JTO.0b013e31827627f8.
The recent findings of the National Lung Screening Trial showed 24.2% of individuals at high risk for lung cancer having one or more indeterminate nodules detected by low-dose computed tomography-based screening, 96.4% of which were eventually confirmed as false positives. These positive scans necessitate additional diagnostic procedures to establish a definitive diagnosis that adds cost and risk to the paradigm. A plasma test able to assign benign versus malignant pathology in high-risk patients would be an invaluable tool to complement low-dose computed tomography-based screening and promote its rapid implementation.
We evaluated 17 biomarkers, previously shown to have value in detecting lung cancer, against a discovery cohort, comprising benign (n = 67) cases and lung cancer (n = 69) cases. A Random Forest method based analysis was used to identify the optimal biomarker panel for assigning disease status, which was then validated against a cohort from the Mayo Clinic, comprising patients with benign (n = 61) or malignant (n = 20) indeterminate lung nodules.
Our discovery efforts produced a seven-analyte plasma biomarker panel consisting of interleukin 6 (IL-6), IL-10, IL-1ra, sIL-2Rα, stromal cell-derived factor-1α+β, tumor necrosis factor α, and macrophage inflammatory protein 1 α. The sensitivity and specificity of our panel in our validation cohort is 95.0% and 23.3%, respectively. The validated negative predictive value of our panel was 93.8%.
We developed a seven-analyte plasma biomarker panel able to identify benign nodules, otherwise deemed indeterminate, with a high degree of accuracy. This panel may have clinical utility in risk-stratifying screen-detected lung nodules, decrease unnecessary follow-up imaging or invasive procedures, and potentially avoid unnecessary morbidity, mortality, and health care costs.
最近的全国肺癌筛查试验结果显示，24.2%的肺癌高危人群通过低剂量计算机断层扫描筛查检测到一个或多个不确定结节，其中 96.4%最终被确认为假阳性。这些阳性扫描需要额外的诊断程序来确定明确的诊断，这给该模式增加了成本和风险。一种能够在高危患者中确定良性与恶性病理的血浆检测方法将是一种非常有价值的工具，可以补充低剂量计算机断层扫描筛查，并促进其快速实施。
我们评估了 17 种生物标志物，这些标志物以前被证明在检测肺癌方面具有价值，针对一个由良性（n=67）病例和肺癌（n=69）病例组成的发现队列。使用基于随机森林方法的分析来确定用于分配疾病状态的最佳生物标志物组合，然后用来自梅奥诊所的一个队列进行验证，该队列包括良性（n=61）或恶性（n=20）不确定的肺结节患者。
我们的发现工作产生了一个由七个分析物组成的血浆生物标志物组合，包括白细胞介素 6（IL-6）、白细胞介素 10（IL-10）、白细胞介素 1 受体拮抗剂（IL-1ra）、可溶性白细胞介素 2 受体α（sIL-2Rα）、基质细胞衍生因子-1α+β（stromal cell-derived factor-1α+β）、肿瘤坏死因子α（tumor necrosis factor α）和巨噬细胞炎性蛋白 1α（macrophage inflammatory protein 1α）。我们验证队列中我们的组合的灵敏度和特异性分别为 95.0%和 23.3%。我们的组合的验证阴性预测值为 93.8%。
我们开发了一种能够以高度准确性识别良性结节的七分析物血浆生物标志物组合，否则这些结节被认为是不确定的。该组合可能具有在筛选检测到的肺结节中进行风险分层的临床实用性，减少不必要的随访影像学或侵入性程序，并可能避免不必要的发病率、死亡率和医疗保健成本。
