Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study
Objective To develop and validate a nomogram for predicting the effectiveness of high-intensity focused ultrasound (HIFU) ablation for uterine fibroids based on oxytocin experiments combined with sonographic features.Methods Sixty patients with uterine fibroids treated with HIFU combined with oxytoc...
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Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Hyperthermia |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/02656736.2024.2436602 |
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| author | Sheng Chen Danling Zhang Guisheng Ding Mengqi Chen Songsong Wu Jianzhong Zou |
| author_facet | Sheng Chen Danling Zhang Guisheng Ding Mengqi Chen Songsong Wu Jianzhong Zou |
| author_sort | Sheng Chen |
| collection | DOAJ |
| description | Objective To develop and validate a nomogram for predicting the effectiveness of high-intensity focused ultrasound (HIFU) ablation for uterine fibroids based on oxytocin experiments combined with sonographic features.Methods Sixty patients with uterine fibroids treated with HIFU combined with oxytocin for uterine fibroids were retrospectively analyzed. Before HIFU treatment, all patients underwent abdominal ultrasonography and oxytocin testing for classification. Predictive factors were selected through univariate and multivariate logistic regression analyses. A predictive model for the clinical efficacy of HIFU treatment of uterine fibroids was established using the R language. The model was visualized by a nomogram, and its discriminative ability, calibration, and clinical value were evaluated.Results Types of myomas, classification of blood flow around the myomas, location of the myomas, and classification of oxytocin were selected as the final predictive factors to construct the model. The calibration curve of the nomogram demonstrated good consistency between actual observations and nomogram predictions, with an absolute error of 0.066. The model’s discriminative ability was evaluated by the area under the curve, which was 0.887 (95% CI: 0.818–0.955). The sensitivity and specificity were 84.4% and 78.8%, respectively, indicating that the model had a good predictive value for the ablation situation. Decision curve analysis showed that the model had high clinical applicability, with the maximum net benefit threshold probability interval ranging from 12.0% to 80.5%.Conclusion The prediction model for HIFU treatment of uterine fibroids, based on ultrasound characteristics and oxytocin test, shows strong predictive ability and may help clinicians choose suitable patients for treatment. |
| format | Article |
| id | doaj-art-ac8e7a08d8b44b52990d7bb555c6a929 |
| institution | Kabale University |
| issn | 0265-6736 1464-5157 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Hyperthermia |
| spelling | doaj-art-ac8e7a08d8b44b52990d7bb555c6a9292025-01-06T02:22:44ZengTaylor & Francis GroupInternational Journal of Hyperthermia0265-67361464-51572025-12-0142110.1080/02656736.2024.2436602Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center studySheng Chen0Danling Zhang1Guisheng Ding2Mengqi Chen3Songsong Wu4Jianzhong Zou5State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical Unibersity, Chongqing, ChinaDepartment of Ultrasonography, Fujian Medical University Union Hospital, Fuzhou, ChinaDepartment of Ultrasonography, Shengli Clinical Medical College of Fujian Medical University, Fujian Provicial Hospital, Fuzhou, ChinaDepartment of Ultrasonography, Shengli Clinical Medical College of Fujian Medical University, Fujian Provicial Hospital, Fuzhou, ChinaDepartment of Ultrasonography, Shengli Clinical Medical College of Fujian Medical University, Fujian Provicial Hospital, Fuzhou, ChinaState Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical Unibersity, Chongqing, ChinaObjective To develop and validate a nomogram for predicting the effectiveness of high-intensity focused ultrasound (HIFU) ablation for uterine fibroids based on oxytocin experiments combined with sonographic features.Methods Sixty patients with uterine fibroids treated with HIFU combined with oxytocin for uterine fibroids were retrospectively analyzed. Before HIFU treatment, all patients underwent abdominal ultrasonography and oxytocin testing for classification. Predictive factors were selected through univariate and multivariate logistic regression analyses. A predictive model for the clinical efficacy of HIFU treatment of uterine fibroids was established using the R language. The model was visualized by a nomogram, and its discriminative ability, calibration, and clinical value were evaluated.Results Types of myomas, classification of blood flow around the myomas, location of the myomas, and classification of oxytocin were selected as the final predictive factors to construct the model. The calibration curve of the nomogram demonstrated good consistency between actual observations and nomogram predictions, with an absolute error of 0.066. The model’s discriminative ability was evaluated by the area under the curve, which was 0.887 (95% CI: 0.818–0.955). The sensitivity and specificity were 84.4% and 78.8%, respectively, indicating that the model had a good predictive value for the ablation situation. Decision curve analysis showed that the model had high clinical applicability, with the maximum net benefit threshold probability interval ranging from 12.0% to 80.5%.Conclusion The prediction model for HIFU treatment of uterine fibroids, based on ultrasound characteristics and oxytocin test, shows strong predictive ability and may help clinicians choose suitable patients for treatment.https://www.tandfonline.com/doi/10.1080/02656736.2024.2436602High-intensity ultrasound (HIFU)uterine fibroidsoxytocin experimentsonographic features |
| spellingShingle | Sheng Chen Danling Zhang Guisheng Ding Mengqi Chen Songsong Wu Jianzhong Zou Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study International Journal of Hyperthermia High-intensity ultrasound (HIFU) uterine fibroids oxytocin experiment sonographic features |
| title | Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study |
| title_full | Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study |
| title_fullStr | Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study |
| title_full_unstemmed | Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study |
| title_short | Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospective single-center study |
| title_sort | nomogram for predicting the efficacy of high intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features a retrospective single center study |
| topic | High-intensity ultrasound (HIFU) uterine fibroids oxytocin experiment sonographic features |
| url | https://www.tandfonline.com/doi/10.1080/02656736.2024.2436602 |
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