关键词: 原发性肝癌, 早期复发, 风险因素, 预测模型

Abstract: Objective To investigate the prevalence and risk factors of early recurrence of primary liver cancer after resection, and to establish a predictive model. Methods From January 2019 to January 2021, 110 patients with primary liver cancer were treated in Beijing You'an Hospital affiliated to Capital Medical University. All patients were followed up for 2 year after operation. According to the followed up results, they were divided into the recurrence group (42 cases) and the non-recurrence group (68 cases). The clinical data were collected, the early recurrence were counted, and the risk factors of early recurrence of primary liver cancer after resection were analyzed by multivariate Cox regression. A nomograph prediction model was constructed to evaluate the predictive value of the model for early postoperative recurrence of primary liver cancer. Results Forty-two of 110 cases suffered from early recurrence of primary liver cancer after resection, the recurrence rate was 38.18%. The result of Cox regression model showed that poorly differentiated tumors, tumor diameter≥5 cm, tumor number≥2, extrahepatic invasion, compensatory stage of cirrhosis, MVI and AFP>400 μg/L were independent risk factors for early postoperative recurrence of primary liver cancer (P<0.05). The C-index of recurrence in patients with primary liver cancer after radical surgery was 0.794±0.054, with a median confidence level of 0.75-0.93, indicating that the accuracy of the model was good. The results of calibration curve show that the predicted probability was close to the actual probability, which indicates that the regression model has good discrimination, calibration and prediction ability. Conclusion There was early recurrence of primary liver cancer after resection, and the risk factors of recurrence include poorly differentiated tumor, tumor diameter ≥5 cm, tumor number ≥2, extrahepatic invasion, compensatory stage of cirrhosis, MVI and AFP>400μg/L, etc. The nomogram constructed based on this can accurately predict the risk of early recurrence of primary liver cancer after surgery, thus had high clinical application value.

Key words: Primary liver cancer, Early recurrence, Risk factors, Prediction model