Background. Lung cancer (LC) is top-ranked in cancer incidence and is the leading cause of cancer death globally. Combining serum biomarkers can improve the accuracy of LC diagnosis. The identification of the best potential combination of traditional tumor markers is essential for LC diagnosis. Patients and Methods. Blood samples were collected from 132 LC cases and 118 benign lung disease (BLD) controls. The expression levels of ten serum tumor markers (CYFR21, CEA, NSE, SCC, CA15-3, CA 19-9, CA 125, CA50, CA242, and CA724) were assayed, and that the expression in the levels of tumor markers were evaluated, isolated, and combined in different patients. The performance of the biomarkers was analyzed by receiver operating characteristic (ROC) analyses, and the difference between combinations of biomarkers was compared by Chi-square () tests. Results. As single markers, CYFR21 and CEA showed good diagnostic efficacy for nonsmall cell lung cancer (NSCLC) patients, while NSE and CEA were the most sensitive in the diagnosis of small cell lung cancer (SCLC). The area under the curve (AUC) value was 0.854 for the panel of four biomarkers (CYFR21, CEA, NSE, and SCC), 0.875 for the panel of six biomarkers (CYFR21, CEA, NSE, SCC, CA125, and CA15-3), and 0.884 for the panel of ten markers (CYFR21, CEA, NSE, SCC, CA125, CA15-3, CA19-9, CA50, CA242, and CA724). With a higher sensitivity and negative predictive value (NPV), the diagnostic accuracy of the three panels was better than that of any single biomarker, but there were no statistically significant differences among them (all values > 0.05). However, the panel of six carbohydrate antigen (CA) biomarkers (CA125, CA15-3, CA19-9, CA50, CA242, and CA724) showed a lower diagnostic value (AUC: 0.776, sensitivity: 59.8%, specificity: 73.0%, and NPV: 60.4%) than the three panels ( value < 0.05). The performance was similar even when analyzed individually by LC subtypes. Conclusion. The biomarkers isolated are elevated for different types of lung cancer, and the panel of CYFR21, CEA, NSE, and SCC seems to be a promising serum biomarker for the diagnosis of lung cancer, while the combination with carbohydrate antigen markers does not improve the diagnostic efficacy.

中文翻译：

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联合碳水化合物抗原标志物对肺癌诊断缺乏疗效

背景。肺癌（LC）在癌症发病率中排名第一，是全球癌症死亡的主要原因。结合血清生物标志物可以提高LC诊断的准确性。识别传统肿瘤标志物的最佳潜在组合对于 LC 诊断至关重要。患者和方法. 从 132 例 LC 病例和 118 例良性肺病 (BLD) 对照中采集血样。测定血清中十种肿瘤标志物（CYFR21、CEA、NSE、SCC、CA15-3、CA 19-9、CA 125、CA50、CA242、CA724）的表达水平，肿瘤标志物水平的表达分别为在不同的患者中进行评估、隔离和组合。通过接受者操作特征 (ROC) 分析分析生物标志物的性能，并通过卡方 ( )检验比较生物标志物组合之间的差异。结果. CYFR21和CEA作为单一标志物对非小细胞肺癌（NSCLC）患者显示出良好的诊断效果，而NSE和CEA对小细胞肺癌（SCLC）的诊断最敏感。四种生物标志物（CYFR21、CEA、NSE 和 SCC）的曲线下面积 (AUC) 值为 0.854，六种生物标志物（CYFR21、CEA、NSE、SCC、CA125 和 CA15-3）的曲线下面积为 0.875 )，十个标记组（CYFR21、CEA、NSE、SCC、CA125、CA15-3、CA19-9、CA50、CA242 和 CA724）为 0.884。由于灵敏度和阴性预测值（NPV）较高，三组的诊断准确性优于任何单一的生物标志物，但它们之间没有统计学上的显着差异（所有值 > 0.05）。然而，六种碳水化合物抗原 (CA) 生物标志物（CA125、CA15-3、CA19-9、CA50、CA242 和 CA724）显示出较低的诊断价值（AUC：0.776，敏感性：59.8%，特异性：73.0%，和 NPV：60.4%）比三个面板（值 < 0.05）。即使按 LC 亚型单独分析，性能也相似。结论。分离的生物标志物对于不同类型的肺癌都有所升高，而 CYFR21、CEA、NSE 和 SCC 组合似乎是用于诊断肺癌的有希望的血清生物标志物，而与碳水化合物抗原标志物的组合并不能提高诊断水平功效。