Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Biosci Rep. 2018 Nov 13;38(6). doi: 10.1042/BSR20180464. Print 2018 Dec 21.
Increasing evidences reveal that inflammation plays a critical role in tumorigenesis and progression. We aimed to develop the nomograms based on inflammatory biomarkers to predict micro-vascular invasion (MVI) and tumor grade in stage I/II hepatocellular carcinoma (HCC). A retrospective cohort of 627 patients with stage I/II HCC between January 2007 and December 2014 was included in the study. Logistic regression was performed to identify the independent risk factors of tumor grade and MVI. The significant predictors including neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), lymphocyte-to-monocyte ratio (LMR), tumor volume age, and tumor size were subsequently incorporated to build the nomograms. The prediction accuracies of the nomograms were evaluated using the area under the receiver operating characteristic (ROC) curve. The independent risk factors for tumor grade were NLR, dNLR, and tumor volume (<0.001, =0.001, and <0.001, respectively), which were assembled into tumor grade nomogram. MVI nomogram was developed by dNLR, LMR, age, and tumor size (<0.001, <0.001, <0.001, and =0.001, respectively) which were the independent predictors for MVI. The area under the ROC curve of nomograms for predicting tumor grade and MVI were 0.727 (95% confidence intervals [CI]: 0.690-0.761) and 0.839 (95% CI: 0.808-0.867), respectively. Patients who had a nomogram score of less than 100 and 79 were considered to have high possibility of moderate grade and have low risks of MVI presence, respectively. We successfully developed nomograms predicting tumor grade and MVI based on inflammatory biomarkers with high accuracy, leading to a rational therapeutic choice for stage I/II HCC.
越来越多的证据表明，炎症在肿瘤发生和进展中起着关键作用。我们旨在开发基于炎症生物标志物的列线图，以预测 I/II 期肝细胞癌 (HCC) 的微血管侵犯 (MVI) 和肿瘤分级。本研究纳入了 2007 年 1 月至 2014 年 12 月期间 I/II 期 HCC 患者的回顾性队列 627 例。采用 logistic 回归确定肿瘤分级和 MVI 的独立危险因素。随后将包括中性粒细胞与淋巴细胞比值 (NLR)、衍生中性粒细胞与淋巴细胞比值 (dNLR)、淋巴细胞与单核细胞比值 (LMR)、肿瘤体积年龄和肿瘤大小在内的显著预测因素纳入列线图。使用受试者工作特征曲线 (ROC) 下面积评估列线图的预测准确性。肿瘤分级的独立危险因素为 NLR、dNLR 和肿瘤体积（<0.001、=0.001 和 <0.001），将其组合成肿瘤分级列线图。MVI 列线图由 dNLR、LMR、年龄和肿瘤大小（<0.001、<0.001、<0.001 和 =0.001）组成，这些是 MVI 的独立预测因素。预测肿瘤分级和 MVI 的列线图的 ROC 曲线下面积分别为 0.727（95%置信区间 [CI]：0.690-0.761）和 0.839（95%CI：0.808-0.867）。如果患者的列线图评分低于 100 和 79，则认为其肿瘤分级为中度的可能性较高，MVI 存在的风险较低。我们成功开发了基于炎症生物标志物的预测肿瘤分级和 MVI 的列线图，具有较高的准确性，为 I/II 期 HCC 的合理治疗选择提供了依据。
