To explore and analyze the risk factors for severe abdominal pain after transcatheter arterial chemotherapy embolization (TACE) in patients with HBV related primary liver cancer, and to construct a Logistic regression predictive model.

A total of 180 patients with HBV related primary liver cancer treated by TACE in Lishui Branch of Zhongda Hospital Affiliated to Southeast University from March 2021 to March 2023 were selected as the study objects. The patients were divided into no/mild abdominal pain group (VAS: 0-3, 45 cases) and severe abdominal pain group (VAS: 4-7, 135 cases) according to the visual analogue scale (VAS) score after TACE. The gender, age, TACE history and other clinical data of the two groups of patients were retrospectively collected and analyzed. SPSS software was used to conduct univariate analysis and binary Logistic regression analysis for postoperative abdominal pain in patients with HBV related primary liver cancer treated with TACE, and a Logistic model was constructed according to the results of factor analysis. ROC curve was used to analyze the prediction efficiency and verify the goodness of fit.

The results of univariate analysis showed that TACE history, vascular invasion, number of tumors, and maximum diameter of tumors were all influencing factors for postoperative severe abdominal pain in patients with HBV related primary liver cancer treated with TACE (P<0.05), and the results of binary Logistic regression analysis showed that TACE history, vascular invasion, number of tumors, and maximum diameter of tumors were all independent risk factors. Constructing a logistic prediction model, the AUC value of the area under the ROC curve was 0.907, 95% CI was 0.854-0.945 (P<0.001), sensitivity was 85.93%, and specificity was 84.44%. Hosmer-Lemeshow test showed good goodness of fit (χ²=7.239, P=0.511).

Severe postoperative abdominal pain in patients with HBV related primary liver cancer treated with TACE is closely related to TACE history, vascular invasion, number of tumors, and maximum tumor diameter. Constructing a predictive model can effectively identify high-risk postoperative abdominal pain patients and reduce the risk of severe abdominal pain.