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基于血清蛋白生物标志物组进行肺癌的辅助诊断。

Auxiliary diagnosis of Lung Cancer on the basis of a Serum Protein Biomarker Panel.

作者信息

Lu Qiong, Jia Zhongwei, Gao Junli, Zheng Meijuan, Gao Junshun, Tong Mingjie, Xia Jinxing, Li Fang, Yang Baoling, Zhang Lili, Wang Bo, Wang Rui, Qiao Jinping, Lou Qinqin, Gao Jinbo, Xu Yuanhong

机构信息

Department of Clinical Laboratory, the First Affiliated Hospital of Anhui Medical University, Hefei, 230031, China.

Cosmos Wisdom Mass Spectrometry Center of Zhejiang University Medical School, Hangzhou, 311200, China.

出版信息

J Cancer. 2021 Mar 15;12(10):2835-2843. doi: 10.7150/jca.57429. eCollection 2021.

Abstract

In this study, we established a serum protein biomarker panel (consisting of Pro-SFTPB, CA125, Cyfra21-1, and CEA) and evaluated the feasibility and performance for the auxiliary diagnosis of lung cancer in the Chinese population. : The current study was a single-center study based on the Chinese population and performed in two cohorts (training cohort and validation cohort). Serum concentrations of Pro-SFTPB, CA125, Cyfra21-1, and CEA were measured by a bead-based flow fluorescence immunoassay. The discrimination performance of the model was assessed using sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC). : For the biomarker panel model, the AUC was 0.88 (95% CI, 0.85-0.91) in the training cohort and 0.90 (95% CI, 0.86-0.92) in the validation data cohort, which was significantly greater than the AUC of each biomarker alone. For the nodule risk model, the AUC was improved to 0.96 (95% CI, 0.94-0.98) in the training cohort and 0.95 (95% CI, 0.93-0.97) in the validation cohort. In addition, the biomarker panel model yielded an AUC of 0.78 (95% CI, 0.74-0.81) for stage I & II lung cancer, better than the performance of individual biomarker alone. : It was demonstrated that 4-protein biomarker panel had a significant performance in identifying lung cancer patients from healthy controls, especially combining with the nodule size. Specifically, it yielded excellent discrimination for identifying early-stage lung cancer patients than individual biomarker alone. A future large-scale study is underway to further define the clinical application of this method for the early diagnosis of lung cancer among Chinese populations.

摘要

在本研究中,我们建立了一个血清蛋白生物标志物组合(由前表面活性蛋白B、癌抗原125、细胞角蛋白19片段和癌胚抗原组成),并评估了其在中国人群中辅助诊断肺癌的可行性和性能。本研究是一项基于中国人群的单中心研究,在两个队列(训练队列和验证队列)中进行。通过基于微珠的流动荧光免疫测定法测量前表面活性蛋白B、癌抗原125、细胞角蛋白19片段和癌胚抗原的血清浓度。使用敏感性、特异性和受试者操作特征(ROC)曲线下面积(AUC)评估模型的鉴别性能。对于生物标志物组合模型,训练队列中的AUC为0.88(95%置信区间,0.85 - 0.91),验证数据队列中的AUC为0.90(95%置信区间,0.86 - 0.92),显著高于每个单独生物标志物的AUC。对于结节风险模型,训练队列中的AUC提高到0.96(95%置信区间,0.94 - 0.98),验证队列中的AUC为0.95(95%置信区间,0.93 - 0.97)。此外,生物标志物组合模型对I期和II期肺癌的AUC为0.78(95%置信区间,0.74 - 0.81),优于单个生物标志物的性能。结果表明,4蛋白生物标志物组合在从健康对照中识别肺癌患者方面具有显著性能,特别是结合结节大小。具体而言,与单个生物标志物相比,它在识别早期肺癌患者方面具有出色的鉴别能力。一项未来的大规模研究正在进行中,以进一步确定该方法在中国人群中早期诊断肺癌的临床应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8428/8040888/4408f5836884/jcav12p2835g001.jpg

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