Aim: To construct an integrated nomogram combining protein induced by vitamin K antagonist-II (PIVKA-II), alpha fetoprotein (AFP) and other clinical factors to detect microvascular invasion (MVI) in early hepatocellular carcinoma (HCC) patients with single nodule.
Methods: One hundred and eleven early HCC patients were enrolled in the present study and 43 early HCC patients were diagnosed with MVI. Serum levels of PIVKA-II, AFP and other laboratory indicators were detected. Chi-squared test, t-test and logistic regression were employed in statistic analysis. A nomogram combining independent predictors was constructed and internal validated.
Results: In early HCC patients with MVI, PIVKA-II serum level was significantly higher than those without MVI (385.97 mAU/ml vs 67.08 mAU/ml; P < 0.01), as well as AFP serum level (81.6 ng/mL vs 9.15 ng/mL P = 0.001). PIVAK-II, AFP serum levels and tumor size were independent risk factors for MVI in early HCC, which was employed to develop a logistic regression model. The area under the ROC curve (AUROC) of the model was 0.74 (95%CI 0.65 - 0.84). A nomogram combining PIVKA-II, AFP and tumor size was constructed and calibration curves showed that the model was accurate in predicting the risk of MVI in early HCC patients.
Conclusion: The present study indicates that a preoperative nomogram combining PIVKA-II, AFP and tumor size could estimate the preoperative probability of MVI in early HCC patients, which may help clinicians in choosing treatment options and prognosis evaluation.


中文翻译：

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预测早期肝细胞癌微血管浸润的列线图


目的：构建结合维生素K拮抗剂-II（PIVKA-II）、甲胎蛋白（AFP）等临床因素诱导蛋白的综合列线图，以检测早期肝细胞癌（HCC）单结节患者的微血管侵犯（MVI）。
方法：本研究招募了 111 名早期 HCC 患者，其中 43 名早期 HCC 患者被诊断为 MVI。检测血清PIVKA-II、AFP等实验室指标水平。统计分析采用卡方检验、t检验和逻辑回归。构建并内部验证了结合独立预测因子的列线图。
结果：在 MVI 的早期 HCC 患者中，PIVKA-II 血清水平显着高于没有 MVI 的患者（385.97 mAU/ml vs 67.08 mAU/ml；P < 0.01），以及 AFP 血清水平（81.6 ng/mL vs 9.15 ng/毫升 P = 0.001）。PIVAK-II、AFP 血清水平和肿瘤大小是早期 HCC 中 MVI 的独立危险因素，用于开发逻辑回归模型。模型的 ROC 曲线下面积 (AUROC) 为 0.74 (95% CI 0.65 - 0.84)。构建了结合 PIVKA-II、AFP 和肿瘤大小的列线图，校准曲线表明该模型能够准确预测早期 HCC 患者发生 MVI 的风险。
结论：本研究表明，结合 PIVKA-II、AFP 和肿瘤大小的术前列线图可以估计早期 HCC 患者 MVI 的术前概率，这可能有助于临床医生选择治疗方案和评估预后。