ObjectiveTo analyze the risk factors and develop a nomagram predictive model for early recurrence after curative resection for hepatocellular carcinoma (HCC). MethodsThe clinicopathologic data of the patients with HCC who underwent radical hepatectomy at the First Affiliated Hospital of Xinjiang Medical University from August 2017 to August 2021 were retrospectively collected. The univariate and multivariate logistic regression analysis were used to screen for the risk factors of early recurrence for HCC after radical hepatectomy, and a nomogram predictive model was established based on the risk factors. The receiver operating characteristic (ROC) curve and calibration curve were used to validate the predictive performance of the model, and the decision curve analysis (DCA) curve was used to evaluate its clinical practicality. ResultsA total of 302 patients were included based on the inclusion and exclusion criteria, and 145 (48.01%) of whom experienced early recurrence. The results of multivariate logistic regression model analysis showed that the preoperative neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), γ-glutamate transferase (GGT), alpha fetoprotein (AFP), tumor size, and microvascular invasion (MVI) were the influencing factors of early recurrence for HCC after radical resection (P<0.05). The nomogram was established based on the risk factors. The area under the ROC curve of the nomogram was 0.858 [95%CI (0.816, 0.899)], and the Brier index of the calibration curve of the nomogram was 0.152. The predicted result of the nomogram was relatively close to the true result (Hosmer-Lemeshow test, P=0.913). The DCA result showed that the clinical net benefit of intervention based on the predicted probability of the model was higher than that of non-intervening in all HCC patients and intervening in all HCC patients when the threshold probability was in the range of 0.1 to 0.8. ConclusionsThe results of this study suggest that for the patients with the risk factors such as preoperative NLR greater than 2.13, PLR greater than 108.15, GGT greater than 46.0 U/L, AFP higher than 18.96 μg/L, tumor size greater than 4.9 cm, and presence of preoperative MVI need to closely pay attention to the postoperative early recurrence. The nomogram predictive model constructed based on these risk factors in this study has a good discrimination and accuracy, and it could obtain clinical net benefit when the threshold probability is 0.1 to 0.8.
Objective To explore the impact of microvascular invasion (MVI) on the survival prognosis of patients after radical hepatectomy for hepatocellular carcinoma, to analyze its related risk factors, and to provide reference and support for the treatment of early postoperative recurrence. MethodsBy searching domestic and international medical literature databases, we screened studies related to MVI in hepatocellular carcinoma, focusing on the definition, grading, risk factors, preoperative prediction methods, and postoperative treatment strategies of MVI, and summarized the results of the existing studies. ResultsMVI is widely recognized as a significant risk factor for the intrahepatic metastasis and early postoperative recurrence of hepatocellular carcinoma. This paper aims to comprehensively investigate the characteristics of MVI and its impact on the postoperative recurrence of hepatocellular carcinoma, with a specific focus on identifying the risk factors associated with MVI. The study encompasses cutting-edge fields such as imaging genomics and genomics, with the objective of providing a scientific foundation for preoperative evaluation. Additionally, the paper examines postoperative treatment strategies for MVI, including comprehensive options such as local therapy, systemic therapy, and antiviral therapy, in order to establish a multidimensional intervention pathway for patients with hepatocellular carcinoma. The ultimate goal is to enhance prognosis and reduce recurrence rates. In the future, further refinement of MVI-related risk factors and optimization of preoperative prediction models, along with the development of personalized postoperative treatment plans, will be crucial areas of focus for hepatocellular carcinoma research and clinical practice. ConclusionsThe study of MVI and its targeted treatment strategies are important for reducing the postoperative recurrence rate of hepatocellular carcinoma and improving patient survival. The preoperative prediction model and postoperative treatment plan should be optimized in the future to provide more effective treatment reference for patients.