Background: Microvascluar invasion and satellite lesion (MS), important unfavourable pathological factors, significantly contribute to tumour recurrence and impair the prognosis in hepatocellular carcinoma. We aimed to construct a model for the prediction of MS in order to plan treatment better.
Methods: A total of 1135 consecutive patients with hepatocellular carcinoma who received radical hepatectomy at West China Hospital were randomly assigned to a training set and a validation set. Multivariate analysis was preformed to identify independent risk factors of MS in the training set, and a nomogram was then constructed based on the risk factors. The concordance index (C-index) and a calibration curve were used to assess the predictive performance of the model.
Results: The occurrence rate of MS was about 36.5%. Based on the multivariate analysis, the following six variables were incorporated into the nomogram: age (hazard ratio (HR): 0.531), alpha fetoprotein (HR: 1.327), neutrophil-to-lymphocyte ratio (>2.8, HR: 1.732), international normalized ratio (>1.07, HR: 1.702), tumour size (HR: 1.116) and tumour number (HR: 1.842). The model showed satisfactory discrimination abilities, with a C-index of 0.721 for the training set and 0.704 for the validation set. The receiver operating characteristic curve confirmed the predictive power. Meanwhile, the calibration curve presented a goodness of fit between prediction of the model and actual observations.
Conclusions: The user-friendly model may be useful for prediction of the occurrence of MS and to plan treatment more rationally preoperatively.
Keywords: hepatectomy; hepatocellular carcinoma; microvascluar invasion and satellite lesion; nomogram.
© 2018 Royal Australasian College of Surgeons.