Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology
© 2023. The Author(s)..
OBJECTIVE: The accurate preoperative differentiation of benign and malignant adnexal masses, especially those with complex ultrasound morphology, remains a great challenge for junior sonographers. The purpose of this study was to develop and validate a nomogram based on the Ovarian-Adnexal Reporting and Data System (O-RADS) for predicting the malignancy risk of adnexal masses with complex ultrasound morphology.
METHODS: A total of 243 patients with data on adnexal masses with complex ultrasound morphology from January 2019 to December 2020 were selected to establish the training cohort, while 106 patients with data from January 2021 to December 2021 served as the validation cohort. Univariate and multivariate analyses were used to determine independent risk factors for malignant tumors in the training cohort. Subsequently, a predictive nomogram model was developed and validated in the validation cohort. The calibration, discrimination, and clinical net benefit of the nomogram model were assessed separately by calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Finally, we compared this model to the O-RADS.
RESULTS: The O-RADS category, an elevated CA125 level, acoustic shadowing and a papillary projection with color Doppler flow were the independent predictors and were incorporated into the nomogram model. The area under the ROC curve (AUC) of the nomogram model was 0.958 (95% CI, 0.932-0.984) in the training cohort. The specificity and sensitivity were 0.939 and 0.893, respectively. This nomogram also showed good discrimination in the validation cohort (AUC = 0.940, 95% CI, 0.899-0.981), with a sensitivity of 0.915 and specificity of 0.797. In addition, the nomogram model showed good calibration efficiency in both the training and validation cohorts. DCA indicated that the nomogram was clinically useful. Furthermore, the nomogram model had higher AUC and net benefit than the O-RADS.
CONCLUSION: The nomogram based on the O-RADS showed a good predictive ability for the malignancy risk of adnexal masses with complex ultrasound morphology and could provide help for junior sonographers.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:16 |
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| Enthalten in: |
Journal of ovarian research - 16(2023), 1 vom: 21. März, Seite 57 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Gong, Li-Ping [VerfasserIn] |
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| Anmerkungen: |
Date Completed 23.03.2023 Date Revised 24.03.2023 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s13048-023-01133-1 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 100 | 1 | |a Gong, Li-Ping |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology |
| 264 | 1 | |c 2023 | |
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| 500 | |a Date Revised 24.03.2023 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023. The Author(s). | ||
| 520 | |a OBJECTIVE: The accurate preoperative differentiation of benign and malignant adnexal masses, especially those with complex ultrasound morphology, remains a great challenge for junior sonographers. The purpose of this study was to develop and validate a nomogram based on the Ovarian-Adnexal Reporting and Data System (O-RADS) for predicting the malignancy risk of adnexal masses with complex ultrasound morphology | ||
| 520 | |a METHODS: A total of 243 patients with data on adnexal masses with complex ultrasound morphology from January 2019 to December 2020 were selected to establish the training cohort, while 106 patients with data from January 2021 to December 2021 served as the validation cohort. Univariate and multivariate analyses were used to determine independent risk factors for malignant tumors in the training cohort. Subsequently, a predictive nomogram model was developed and validated in the validation cohort. The calibration, discrimination, and clinical net benefit of the nomogram model were assessed separately by calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Finally, we compared this model to the O-RADS | ||
| 520 | |a RESULTS: The O-RADS category, an elevated CA125 level, acoustic shadowing and a papillary projection with color Doppler flow were the independent predictors and were incorporated into the nomogram model. The area under the ROC curve (AUC) of the nomogram model was 0.958 (95% CI, 0.932-0.984) in the training cohort. The specificity and sensitivity were 0.939 and 0.893, respectively. This nomogram also showed good discrimination in the validation cohort (AUC = 0.940, 95% CI, 0.899-0.981), with a sensitivity of 0.915 and specificity of 0.797. In addition, the nomogram model showed good calibration efficiency in both the training and validation cohorts. DCA indicated that the nomogram was clinically useful. Furthermore, the nomogram model had higher AUC and net benefit than the O-RADS | ||
| 520 | |a CONCLUSION: The nomogram based on the O-RADS showed a good predictive ability for the malignancy risk of adnexal masses with complex ultrasound morphology and could provide help for junior sonographers | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Adnexal masses | |
| 650 | 4 | |a CA125 | |
| 650 | 4 | |a Nomogram | |
| 650 | 4 | |a O-RADS | |
| 700 | 1 | |a Li, Xiao-Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Ying-Nan |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Shuang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Shuang |e verfasserin |4 aut | |
| 700 | 1 | |a Feng, Ya-Nan |e verfasserin |4 aut | |
| 700 | 1 | |a Lv, Ya-Er |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Xi-Juan |e verfasserin |4 aut | |
| 700 | 1 | |a Peng, Yan-Qing |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Xiao-Shan |e verfasserin |4 aut | |
| 700 | 1 | |a Tian, Jia-Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Cong-Xin |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Li-Tao |e verfasserin |4 aut | |
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