American journal of translational research · 2025
Development and validation of a nomogram for predicting moderate-to-severe pain in hepatitis B virus-related liver cancer patients after CyberKnife treatment.
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Chi Yating, Yang Jing, Li Guona, Jia Jun
Аннотация
OBJECTIVE: To identify risk factors for moderate-to-severe pain after CyberKnife treatment in patients with hepatitis B virus - related liver cancer and to develop a predictive nomogram.
METHODS: This retrospective study included 169 patients treated between April 2021 and August 2022 as the derivation cohort, and 132 patients treated between September 2022 and October 2024 as the validation cohort, all at the Fifth Medical Center of Chinese PLA General Hospital. Univariate and multivariate logistic regression analyses were conducted in the derivation cohort to identify independent predictors, which were then incorporated into a nomogram. Predictive performance was evaluated using receiver operating characteristic (ROC) curves in both cohorts.
RESULTS: Moderate-to-severe postoperative pain occurred in 57/169 patients (33.73%) in the derivation cohort and 45/132 (34.09%) in the validation cohort. Multivariate analysis identified four independent risk factors: tumor invasion of the liver capsule, Child-Pugh class B, cirrhosis, and tumor size ≥5 cm (all P<0.05). The nomogram achieved an AUC of 0.700 in the derivation cohort and 0.685 in the validation cohort, indicating acceptable discrimination.
CONCLUSIONS: Tumor proximity to the liver capsule, impaired baseline liver function, cirrhosis, and large tumor size were significant predictors of moderate-to-severe postoperative pain after CyberKnife treatment. The developed nomogram demonstrated robust internal and external validity, offering a practical tool for preoperative risk stratification and individualized analgesic planning.
METHODS: This retrospective study included 169 patients treated between April 2021 and August 2022 as the derivation cohort, and 132 patients treated between September 2022 and October 2024 as the validation cohort, all at the Fifth Medical Center of Chinese PLA General Hospital. Univariate and multivariate logistic regression analyses were conducted in the derivation cohort to identify independent predictors, which were then incorporated into a nomogram. Predictive performance was evaluated using receiver operating characteristic (ROC) curves in both cohorts.
RESULTS: Moderate-to-severe postoperative pain occurred in 57/169 patients (33.73%) in the derivation cohort and 45/132 (34.09%) in the validation cohort. Multivariate analysis identified four independent risk factors: tumor invasion of the liver capsule, Child-Pugh class B, cirrhosis, and tumor size ≥5 cm (all P<0.05). The nomogram achieved an AUC of 0.700 in the derivation cohort and 0.685 in the validation cohort, indicating acceptable discrimination.
CONCLUSIONS: Tumor proximity to the liver capsule, impaired baseline liver function, cirrhosis, and large tumor size were significant predictors of moderate-to-severe postoperative pain after CyberKnife treatment. The developed nomogram demonstrated robust internal and external validity, offering a practical tool for preoperative risk stratification and individualized analgesic planning.