Burns : journal of the International Society for Burn Injuries · 2026
Predicting response to ³²P patch brachytherapy in pathological scars: A model integrating multimodal ultrasound and clinical features.
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Cao Liu-Liu, Bi Yu, Zhang Gang, Li Fei, Jiang Fan
Аннотация
OBJECTIVE: To develop and validate a predictive model integrating ultrasound features and clinical characteristics for assessing the efficacy of ³²P patch brachytherapy in pathological scars.
METHODS: A total of 48 patients with pathological scars (yielding 169 total lesions) who received ³²P patch brachytherapy at the Department of Nuclear Medicine, the Second Affiliated Hospital of Anhui Medical University (April 1, 2023 - December 31, 2025) were retrospectively analyzed. The patients were randomly divided into a training set and an internal validation set at an approximate 7:3 ratio, yielding 119 and 50 lesions, respectively. Lesions in each set were further divided into an effective group and an ineffective group based on the therapeutic response. Univariate mixed-effects logistic regression analysis was employed to compare ultrasound and clinical characteristics between the two groups. Variables with statistical significance were entered into a multivariate mixed-effects logistic regression analysis to identify independent predictors of treatment efficacy and to construct a predictive model. The discriminative performance of the model was internally validated using the validation set.
RESULTS: Scar thickness, vascular index (VI), disease duration, and mean shear wave velocity (SWV) were identified as independent predictors of the efficacy of ³²P patch brachytherapy in pathological scars (all P < 0.05). The predictive model demonstrated an area under the ROC curve (AUC) of 0.969 (95% CI: 0.944-0.994) in the training set. The calibration curve indicated good agreement between predicted and observed outcomes (χ² = 3.598, P = 0.891). Internal validation in the validation set yielded an AUC of 0.790(95% CI: 0.664-0.916).
CONCLUSION: A multivariable regression model incorporating scar thickness, VI, disease duration, and mean SWV provides a reliable tool for predicting the efficacy of ³²P patch brachytherapy for pathological scars. This model may assist in optimizing clinical treatment strategies and reducing potential short- and long-term risks associated with radiotherapy.
METHODS: A total of 48 patients with pathological scars (yielding 169 total lesions) who received ³²P patch brachytherapy at the Department of Nuclear Medicine, the Second Affiliated Hospital of Anhui Medical University (April 1, 2023 - December 31, 2025) were retrospectively analyzed. The patients were randomly divided into a training set and an internal validation set at an approximate 7:3 ratio, yielding 119 and 50 lesions, respectively. Lesions in each set were further divided into an effective group and an ineffective group based on the therapeutic response. Univariate mixed-effects logistic regression analysis was employed to compare ultrasound and clinical characteristics between the two groups. Variables with statistical significance were entered into a multivariate mixed-effects logistic regression analysis to identify independent predictors of treatment efficacy and to construct a predictive model. The discriminative performance of the model was internally validated using the validation set.
RESULTS: Scar thickness, vascular index (VI), disease duration, and mean shear wave velocity (SWV) were identified as independent predictors of the efficacy of ³²P patch brachytherapy in pathological scars (all P < 0.05). The predictive model demonstrated an area under the ROC curve (AUC) of 0.969 (95% CI: 0.944-0.994) in the training set. The calibration curve indicated good agreement between predicted and observed outcomes (χ² = 3.598, P = 0.891). Internal validation in the validation set yielded an AUC of 0.790(95% CI: 0.664-0.916).
CONCLUSION: A multivariable regression model incorporating scar thickness, VI, disease duration, and mean SWV provides a reliable tool for predicting the efficacy of ³²P patch brachytherapy for pathological scars. This model may assist in optimizing clinical treatment strategies and reducing potential short- and long-term risks associated with radiotherapy.