BACKGROUND Vessels that encapsulate tumor cluster (VETC) is associated with poor prognosis in hepatocellular carcinoma (HCC). Vessels that encapsulate tumor cluster estimation before initial treatment is helpful for clinical doctors. We aimed to construct a novel predictive model for VETC, using preoperatively accessible clinical parameters and imagine features. METHODS Totally, 365 HCC patients who received curative hepatectomy in the Sun Yat-Sen University Cancer Center from 2013 to 2014 were enrolled in this study. Vessels that encapsulate tumor cluster pattern was confirmed by immunochemistry staining. 243 were randomly assigned to the training cohort while the rest was assigned to the validation cohort. Independent predictive factors for VETC estimation were determined by univariate and multivariate logistic analysis. We further constructed a predictive nomogram for VETC in HCC. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curve, and calibration curve. Besides, the decision curve was plotted to evaluate the clinical usefulness. Ultimately, Kaplan-Meier survival curves were utilized to confirm the association between the nomogram and survival. RESULTS Immunochemistry staining revealed VETC in 87 patients (23.8%). lymphocyte to monocyte ratio (>7.75, OR = 4.06), neutrophil (>7, OR = 4.48), AST to ALT ratio (AAR > .86, OR = 2.16), ALT to lymphocyte ratio index (BLRI > 21.73, OR = 2.57), alpha-fetoprotein (OR = 1.1), and tumor diameter (OR = 2.65) were independent predictive factors. The nomogram incorporating these predictive factors performed well with an area under the curve (AUC) of .746 and .707 in training and validation cohorts, respectively. Calibration curves indicated the predicted probabilities closely corresponded with the actual VETC status. Moreover, the decision curve proved our nomogram could provide clinical benefits with patients. Finally, low probability of VETC group had significantly longer recurrence free survival (RFS) and overall survival (OS) than the high probability of the VETC group (all P < .001). CONCLUSION A novel predictive nomogram integrating clinical indicators and image characteristics shows strong predictive VETC performance and might provide standardized net clinical benefits.

中文翻译：

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用于预测肝细胞癌中包裹肿瘤簇的血管的新型列线图的开发和验证。

背景技术包封肿瘤簇（VETC）的血管与肝细胞癌（HCC）的不良预后相关。在初次治疗前对肿瘤簇进行封装的血管对临床医生有帮助。我们的目标是利用术前可获得的临床参数和想象特征构建一种新型的 VETC 预测模型。方法选取2013年至2014年在中山大学肿瘤防治中心接受根治性肝切除术的365例HCC患者作为研究对象。通过免疫化学染色确认封装肿瘤簇模式的血管。243 人被随机分配到训练队列，其余则分配到验证队列。VETC 估计的独立预测因素通过单变量和多变量逻辑分析确定。我们进一步构建了 HCC 中 VETC 的预测列线图。列线图的性能通过 C 指数、受试者工作特征 (ROC) 曲线和校准曲线进行评估。此外，还绘制了决策曲线来评估临床实用性。最终，Kaplan-Meier 生存曲线被用来确认列线图和生存之间的关联。结果 免疫化学染色显示 87 名患者 (23.8%) 存在 VETC。淋巴细胞与单核细胞比率 (>7.75，OR = 4.06)、中性粒细胞 (>7，OR = 4.48)、AST 与 ALT 比率 (AAR > .86，OR = 2.16)、ALT 与淋巴细胞比率指数 (BLRI > 21.73，OR = 2.57）、甲胎蛋白（OR = 1.1）和肿瘤直径（OR = 2.65）是独立的预测因素。包含这些预测因素的列线图在训练和验证队列中表现良好，曲线下面积 (AUC) 分别为 0.746 和 0.707。校准曲线表明预测概率与实际 VETC 状态密切相关。此外，决策曲线证明我们的列线图可以为患者提供临床益处。最后，低概率 VETC 组的无复发生存期 (RFS) 和总生存期 (OS) 明显长于高概率 VETC 组（均 P < .001）。结论 整合临床指标和图像特征的新型预测列线图显示出强大的预测 VETC 性能，并可能提供标准化的净临床效益。