联合癌胚抗原、鳞状细胞癌相关抗原、CYFRA 21-1、神经元特异性烯醇酶、组织多肽抗原、原胃泌素释放肽在小细胞肺癌鉴别中的诊断价值。

IF 2.3 4区 医学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Zhimao Chen, Xiangzheng Liu, Xueqian Shang, Kang Qi, Shijie Zhang
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引用次数: 12

摘要

背景:探讨6种肿瘤标志物的诊断价值,并探讨这些肿瘤标志物在鉴别小细胞肺癌中的合适组合。方法:对1938年疑似肺癌患者进行回顾性分析。选择癌胚抗原(CEA)、鳞状细胞癌相关抗原(SCC)、细胞角蛋白19片段21-1 (CYFRA 21-1)、神经元特异性烯醇酶(NSE)、组织多肽抗原(TPA)和原胃泌素释放肽(ProGRP)等候选肿瘤标志物构建logistic回归模型。采用受试者工作特征曲线评价肿瘤标志物的诊断价值和预测模型。结果:ProGRP在确诊的小细胞肺癌中阳性率最高(72.3%),其次是神经元特异性烯醇酶(68.3%)、CYFRA21-1(50.5%)、癌胚抗原(45.5%)、组织多肽抗原(30.7%)和鳞状细胞癌相关抗原(5.9%)。建立了小细胞肺癌鉴别的预测模型,其曲线下面积最高(0.888;95%可信区间:0.846 ~ 0.929),敏感性为71.3%,特异性为95.0%,阳性预测值为49.0%,阴性预测值为98.0%。结论:结合肿瘤标志物可提高小细胞肺癌的鉴别效果。建立了小细胞肺癌鉴别诊断的预测模型,具有较好的疗效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The diagnostic value of the combination of carcinoembryonic antigen, squamous cell carcinoma-related antigen, CYFRA 21-1, neuron-specific enolase, tissue polypeptide antigen, and progastrin-releasing peptide in small cell lung cancer discrimination.

Background: The diagnostic value of six tumor markers was investigated and the appropriate combinations of those tumor markers to discriminate small cell lung cancer was explored.

Methods: Patients suspected with lung cancer (1938) were retrospectively analyzed. Candidate tumor markers from carcinoembryonic antigen (CEA), squamous cell carcinoma-related antigen (SCC), cytokeratin 19 fragment 21-1 (CYFRA 21-1), neuron-specific enolase (NSE), tissue polypeptide antigen (TPA), and progastrin releasing peptide (ProGRP) were selected to construct a logistic regression model. The receiver operating characteristic curve was used for evaluating the diagnostic value of the tumor markers and the predictive model.

Results: ProGRP had the highest positive rate (72.3%) in diagnosed small cell lung cancer, followed by neuron-specific enolase (68.3%), CYFRA21-1 (50.5%), carcinoembryonic antigen (45.5%), tissue polypeptide antigen (30.7%), and squamous cell carcinoma-related antigen (5.9%). The predictive model for small cell lung cancer discrimination was established, which yielded the highest area under the curve (0.888; 95% confidence interval: 0.846-0.929), with a sensitivity of 71.3%, a specificity of 95.0%, a positive predictive value of 49.0%, and a negative predictive value of 98.0%.

Conclusions: Combining tumor markers can improve the efficacy for small cell lung cancer discrimination. A predictive model has been established in small cell lung cancer differential diagnosis with preferable efficacy.

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来源期刊
International Journal of Biological Markers
International Journal of Biological Markers 医学-生物工程与应用微生物
CiteScore
4.10
自引率
0.00%
发文量
43
期刊介绍: IJBM is an international, online only, peer-reviewed Journal, which publishes original research and critical reviews primarily focused on cancer biomarkers. IJBM targets advanced topics regarding the application of biomarkers in oncology and is dedicated to solid tumors in adult subjects. The clinical scenarios of interests are screening and early diagnosis of cancer, prognostic assessment, prediction of the response to and monitoring of treatment.
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