Voronova Veronika, Glybochko Peter, Svistunov Andrey, Fomin Viktor, Kopylov Philipp, Tzarkov Peter, Egorov Alexey, Gitel Evgenij, Ragimov Aligeydar, Boroda Alexander, Poddubskaya Elena, Sekacheva Marina
M&S Decisions LLC, Moscow, Russia.
I.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Front Oncol. 2020 May 22;10:832. doi: 10.3389/fonc.2020.00832. eCollection 2020.
Blood-based tests have been shown to be an effective strategy for colorectal cancer (CRC) detection in screening programs. This study was aimed to test the performance of 20 blood markers including tumor antigens, inflammatory markers, and apolipoproteins as well as their combinations. In total 203 healthy volunteers and 102 patients with CRC were enrolled into the study. Differences between healthy and cancer subjects were evaluated using Wilcoxon rank-sum test. Several multivariate classification algorithms were employed using information about different combinations of biomarkers altered in CRC patients as well as age and gender of the subjects; random sub-sampling cross-validation was done to overcome overfitting problem. Diagnostic performance of single biomarkers and multivariate classification models was evaluated by receiver operating characteristic (ROC) analysis. Of 20 biomarkers, 16 were significantly different between the groups (-value ≤ 0.001); ApoA1, ApoA2 and ApoA4 levels were decreased, whereas levels of tumor antigens (. carcinoembriogenic antigen) and inflammatory markers (e.g., C-reactive protein) were increased in CRC patients vs. healthy subjects. Combinatorial markers including information about all 16 significant analytes, age and gender of patients, demonstrated better performance over single biomarkers with average accuracy on test datasets ≥95% and area under ROC curve (AUROC) ≥98%. Combinatorial approach was shown to be a valid strategy to improve performance of blood-based CRC diagnostics. Further evaluation of the proposed models in screening programs will be performed to gain a better understanding of their diagnostic value.
血液检测已被证明是筛查项目中检测结直肠癌（CRC）的有效策略。本研究旨在测试20种血液标志物的性能，包括肿瘤抗原、炎症标志物和载脂蛋白及其组合。共有203名健康志愿者和102名CRC患者纳入本研究。使用Wilcoxon秩和检验评估健康受试者和癌症受试者之间的差异。采用几种多变量分类算法，利用CRC患者中改变的生物标志物的不同组合以及受试者的年龄和性别信息；进行随机子采样交叉验证以克服过拟合问题。通过受试者工作特征（ROC）分析评估单一生物标志物和多变量分类模型的诊断性能。在20种生物标志物中，两组之间有16种存在显著差异（P值≤0.001）；与健康受试者相比，CRC患者的载脂蛋白A1、载脂蛋白A2和载脂蛋白A4水平降低，而肿瘤抗原（如癌胚抗原）和炎症标志物（如C反应蛋白）水平升高。包含所有16种重要分析物信息、患者年龄和性别的组合标志物在测试数据集上的平均准确率≥95%，ROC曲线下面积（AUROC）≥98%，表现优于单一生物标志物。组合方法被证明是提高基于血液的CRC诊断性能的有效策略。将在筛查项目中对所提出的模型进行进一步评估，以更好地了解其诊断价值。
