Scoring system for predicting postoperative pain after transarterial chemoembolization treatment in liver cancer

Abstract Purpose: Patients that experience severe postoperative pain are more reluctant to adhere the treatment. This study intends to identify the relevant risk factors and construct a scoring system for prediction. Materials and methods: Liver cancer patients that underwent the first TACE treatment at the Second Affiliated Hospital of Chongqing Medical University from January 2019 to December 2020 were collected. The 11-point numerical rating scale (NRS-11) was utilized to evaluate the patient's pain level. The patients were randomly divided into a training and a validation cohort. In the training cohort, the correlation between each parameter and the pain level after TACE was evaluated through logistic regression, and a risk prediction model was established. Finally, the predictive power of the model was verified in the validation cohort. Results: A total of 255 patients with liver cancer were included. In the training cohort, univariate analysis found postoperative pain was related to tumor number, tumor size, microsphere volume, and operation time. The above variables were then incorporated into the multivariate analysis to construct the prediction model, In the training and validation cohorts, the area under the curve (AUC) of the model used to predict moderate to severe pain response after TACE was 0.71 and 0.74, respectively. Additionally, we also created a nomogram for clinical use, patients with a total score greater than 72.90 are considered at a high risk of experiencing moderate to severe pain following TACE. Conclusion: This study successfully constructed and validated a scoring system for predicting moderate to severe pain after an initial TACE treatment.