Analysis and prediction model construction of infection after transcatheter arterial chemoembolization in hepatocellular carcinoma patients

Objective To analyze the risk factors of infectious in hepatocellular carcinoma (HCC) patients after transcatheter arterial chemoembolization (TACE), and construct a prediction model.Methods The complete clinical data of HCC patients who received TACE treatment in the department of Interventional Pain of the Second Affiliated Hospital of the Air Force Medical University from January 1, 2020 to December 31, 2023 were retrospectively analyzed. According to whether infection occurred within 30 days after TACE, the patients were divided into the infection group and the non-infection group. According to the visiting time of HCC patients undergoing TACE, they were divided into the training and validation cohorts. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a prediction model. The area under the curve (AUC) of the receiver operating characteristic curve, calibration curve analysis (CCA) and the Brier score, decision curves analysis (DCA) were used to evaluate the performence of the prediction model.Results A total of 592 HCC patients with TACE were included, the infection rate after TACE was 10.30%, with Gram-negative bacteria was most common infection (55.41%). Comorbid diabetes [OR=12.694, 95%CI(4.415, 36.497)], maximum lesion diameter > 5 cm [OR=7.620, 95%CI(1.994, 29.111)], ascites[OR=5.106, 95%CI(2.226, 11.711)], intraoperative blood loss ≥ 500 mL [OR=20.588, 95%CI(7.269, 58.311)], and operation time≥120 minutes [OR=1.284, 95%CI(1.093, 1.872)] were independent risk factors for post-TACE infection. The AUC of the prediction model in the training set and the validation set were 0.907 and 0.931. CCA showed good consistency of the "predicted probability" and the "actual probability" of the post-TACE infection prediction model, and the Brier scores in the training set and the validation set were 0.084 and 0.075. The DCA curve suggested that the prediction model provided good clinical net benefit.Conclusion Comorbid diabetes, maximum lesion diameter > 5 cm, ascites, intraoperative blood loss ≥ 500 mL, and operation time ≥ 120 minutes were independent risk factors for post-TACE infection. The post- TACE infection prediction model can better identify the occurrence of TACE infection in HCC patients and is a useful tool for early identification of post-TACE infection.