A Nomogram Estimation for the Risk of Microvascular Invasion in Hepatocellular Carcinoma Patients Meeting the Milan Criteria

Abstract

Objective We aimed to develop and validate a nomogram for preoperatively estimating the risk of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) within the Milan criteria. Methods The clinical data of 312 HCC patients who underwent liver surgery at the xxx from Jan 2017 to Dec 2019 were retrospectively collected. Then, the study population was categorized into the training and validation group based on the date of surgery. To identify risk factors related to MVI, we conducted a series of logistic regression analyses. By combining these risk factors, a nomogram was then established. We further clarified the usability of our model through the area under the ROC curve (AUC), decision curve analysis (DCA), and calibration curve. Results Pathological examination revealed MVI in 108 patients with HCC (34.6%). Three independent predictors were identified: level of alpha-fetoprotein (AFP) exceeds 194 ng/mL (OR = 2.20, 95% CI: 1.13-4.31, p = 0.021), size of tumor (OR = 1.59; 95% CI: 1.18-2.12; P < 0.001) and number of tumors (OR = 3.37, 95% CI: 1.64-7.28, p < 0.001). A nomogram was subsequently built with an AUC of 0.73 and 0.74 respectively in the training cohort and validation cohort. The calibration curve showed a relatively high consistency between predicted probability and observed outcomes. Besides, the DCA revealed that the model was clinically beneficial for preoperatively predicting MVI in HCC. Conclusions A model for evaluating the risk of MVI HCC patients was developed and validated. The model could provide clinicians with a relatively reliable basis for optimizing treatment decisions.