Influencing Factors Of Microvascular Invasion In Hepatocellular Carcinoma And Development Of Nomograph Model Of Predicting Before Operation

Objective: Microvascular infiltration(MVI)is one of the important risk factors that affect the low survival rate and early postoperative recurrence of hepatocellular carcinoma(HCC)patients.Unlike large vessel invasion,the diagnosis of MVI can usually only be judged by the results of postoperative histopathological examination.Therefore,exploring the influencing factors of MVI occurrence and evaluating whether HCC patients are complicated with MVI before surgery are crucial for clinical treatment decision-making.Histogram is a widely used statistical model for cancer prognosis prediction and risk assessment,with high accuracy and good discrimination ability.It can generate the probability of clinical events for a single patient.Therefore,developing a nomograph model based on clinical laboratory indices may have potential application prospects in early prediction of MVI risk in HCC.The purpose of this study was to explore the influencing factors of MVI in HCC and to construct a preoperative predictive nomograph model to predict the risk of MVI in HCC patients before surgery.Method: Using a retrospective clinical study method,a total of 424 patients with HCC who received radical hepatectomy from the Hepatobiliary Pancreatic Surgery Department of the Affiliated Hospital of Guilin Medical College from September 2012 to April 2018 were enrolled in the study.The independent risk factors for MVI were identified through logistic regression analysis,and the risk of MVI was estimated by constructing a nomograph model.Using the receiver operating characcteristic curve(ROC),concordance index(c-index),calibration curve,and decision curve analysis(DCA)to evaluate predictive effectiveness.Result: Prealbumin(PAB)≤ 200 mg/L,tumor size > 5 cm,γ-Glutamate transpeptidase(GGT)> 45 U/L and alpha fetoprotein(AFP)> 200 ng/m L are independent risk factors for MVI in HCC.A nomograph model composed of these four variables predicts the risk of MVI,with an area under the ROC curve(AUC)of 0.775(C index 0.781)in the training cohort and 0.787(C index 0.785)in the validation cohort.The nomograph model shows good predictive performance,and the decision curve analysis shows that the nomograph model has certain clinical applicability.Conclusion: We have developed a new nomograph model that uses basic clinical and laboratory variables to predict the probability of preoperative MVI in HCC patients.The nomograph model can help clinicians choose more suitable treatment methods and means.