Development of a nomogram for predicting microvascular invasion in patients with hepatocellular carcinoma.

[BACKGROUND] Preoperative diagnosis of microvascular invasion (MVI) is difficult for patients with hepatocellular carcinoma (HCC). The aim of this study was to develop and validate a nomogram to predict the risk of MVI before surgery.

[METHODS] A total of 661 HCC patients who underwent curative resection were included in the study. Independent risk factors were identified by univariate/multivariate analyses and were built into a nomogram to estimate the risk of MVI. The receiver operating characteristic (ROC) curve, concordance index (c-index), calibration curve and decision curve analysis were used to evaluate the predictive performance of the models.

[RESULTS] Prealbumin, gamma-glutamyl transpeptidase, alpha-fetoprotein level, and tumor size were found to be independent risk factors for MVI and formed the basis of the nomogram. The area under the ROC curve (AUC) of the nomogram for predicting MVI was 0.775 (C-index of 0.781) in the training cohort, 0.787 (C-index of 0.785) in the validation cohort, and 0.789 (C-index of 0.790) in the external validation cohort. The nomogram exhibited favorable calibration performance, and decision curve analysis demonstrated that the nomogram has clinical value.

[CONCLUSIONS] We developed a new nomogram that used basic clinical and laboratory variables to predict the probability of MVI before surgery for HCC patients. This nomogram can help clinicians choose appropriate treatment procedures.