首页> 外文期刊>Clinical proteomics. >Clinical validation of a blood-based classifier for diagnostic evaluation of asymptomatic individuals with pulmonary nodules
【24h】

Clinical validation of a blood-based classifier for diagnostic evaluation of asymptomatic individuals with pulmonary nodules

机译:基于血液的分类器对无症状肺结节患者的诊断评估的临床验证

获取原文
           

摘要

Background The number of pulmonary nodules detected in the US is expected to increase substantially following recent recommendations for nationwide CT-based lung cancer screening. Given the low specificity of CT screening, non-invasive adjuvant methods are needed to differentiate cancerous lesions from benign nodules to help avoid unnecessary invasive procedures in the asymptomatic population. We have constructed a serum-based multi-biomarker panel and assessed its clinical accuracy in a retrospective analysis of samples collected from participants with suspicious radiographic findings in the Prostate, Lung, Chest and Ovarian (PLCO) cancer screening trial. Methods Starting with a set of 9 candidate biomarkers, we identified 8 that exhibited limited pre-analytical variability with increasing clotting time, a key pre-analytical variable associated with the collection of serum. These 8 biomarkers were evaluated in a training study consisting of 95 stage I NSCLC patients and 186 smoker controls where a 5-biomarker pulmonary nodule classifier (PNC) was selected. The clinical accuracy of the PNC was determined in a blinded study of asymptomatic individuals comprising 119 confirmed malignant nodule cases and 119 benign nodule controls selected from the PLCO screening trial. Results A PNC comprising 5 biomarkers: CEA, CYFRA 21-1, OPN, SCC, and TFPI, was selected in the training study. In an independent validation study, the PNC resolved lung cancer cases from benign nodule controls with an AUC of 0.653 (p Conclusions A 5-biomarker blood test has been developed for the diagnostic evaluation of asymptomatic individuals with solitary pulmonary nodules.
机译:背景技术根据最近针对基于CT的全国性肺癌筛查的建议,在美国检测到的肺结节的数量预计将大大增加。鉴于CT筛查的特异性低,需要采用非侵入性辅助方法将癌性病变与良性结节区分开,以帮助避免无症状人群中不必要的侵入性操作。我们已经建立了一个基于血清的多生物标志物检测小组,并通过对从前列腺癌,肺癌,胸腺癌和卵巢癌(PLCO)癌症筛查试验中可疑放射影像学发现的参与者的样本进行回顾性分析,评估了其临床准确性。方法从一组9种候选生物标志物开始,我们鉴定出8种具有有限的分析前变异性,且凝血时间增加,这是与血清收集有关的关键分析前变量。在一项训练研究中对这8种生物标志物进行了评估,该研究包括95位I期非小细胞肺癌患者和186名吸烟对照,其中选择了5种生物标志物肺结节分类器(PNC)。 PNC的临床准确性是在无症状个体的盲研究中确定的,这些个体包括从PLCO筛查试验中选择的119例确诊的恶性结节病例和119例良性结节对照。结果在训练研究中选择了包含5种生物标志物的PNC:CEA,CYFRA 21-1,OPN,SCC和TFPI。在一项独立的验证研究中,PNC从良性结节对照中分离出肺癌病例,AUC为0.653(p结论已经开发了一种5生物标志物的血液测试方法,用于对无症状的孤立性肺结节患者进行诊断评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号