Construction and Validation of Prediction Model of Severe Abdominal Pain Post-Transarterial Chemoembolization in Patients with HBV-Associated Primary Liver Cancer. (30th July 2022)

• Record Type: Journal Article
• Authors: Yang, Yaobo; Chen, Sipan; Yan, Zhaoyong; Jiao, Yang; Yan, Xiang; Li, Yulong
• Other Names: Zheng Pan Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2022(2022)
• Publication Date: 2022-07-30
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2022/5203166
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : Objective . This study is aimed at constructing and evaluating a prediction model of severe abdominal pain post-transcatheter arterial chemoembolization in patients with HBV-related primary liver cancer. Methods . Patients with HBV-associated primary liver cancer who received transarterial chemoembolization (TACE) from March 2019 to March 2022 in the Interventional Therapy Department of our hospital were selected as the subjects, and the included 160 patients were randomly divided into modeling group (n = 120 ) and validation group (n = 40 ) in a ratio of 3 : 1. Visual analog scale (VAS) was used to assess pain severity. 120 patients in the modeling group were divided into no/mild abdominal pain group and severe abdominal pain group. The clinical data of the patients, including gender, age, TACE treatment history, vascular invasion, maximum diameter of tumor, infarction degree, preoperative Eastern Oncology Collaboration Group (ECOG) score, and Lipiodol dosage, were analyzed. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the prediction model for severe abdominal pain post-TACE. Results . A total of 116 patients (72.50%) had severe abdominal pain after TACE. Univariate analysis showed that severe abdominal pain after TACE in the modeling group was associated with TACE treatment history, maximum tumor diameter, infarction degree, and preoperative ECOG score (all P < 0.05 ), but not related to gender, age, vascular invasion, and Lipiodol dosage (all P > 0.05 ). Logistic regression analysis showed that TACE treatment history, maximum tumor diameter, infarction degree, and preoperative ECOG score were all independent influencing factors for acute abdominal pain post-TACE in HBV-HCC patients (all P < 0.05 ). The prediction model equation was Y = − 3.673 + 1.722 × TACE treatment history + 1.175 × tumor maximum diameter + 2.064 × infarction degree + 1.555 × preoperative ECOG score . Goodness-of-fit test results showed no significant difference between the established prediction model and the observed value (χ 2 = 1.645, P = 0.560 ) and R 2 = 0.821, suggesting that the prediction ability of the model was relatively accurate. ROC analysis results showed that the area under the curve (AUC) of severe abdominal pain after TACE was 0.916 (0.862~0.970) and 0.902 (95% CI: 0.841~0.963) in the modeling group and the verification group, respectively. Conclusion . TACE treatment history, tumor maximum diameter, infarction degree, and preoperative ECOG score are independent influencing factors for severe abdominal pain post-TACE in patients with HBV-HCC, and the prediction model established on this basis has good application value.