ArticleUltrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology2017
Estimating risk of malignancy in adnexal masses: external validation of the ADNEX model and comparison with other frequently used ultrasound methods.
Article in Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 4 of them syntheses that pooled it.
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51 citing papers in PubMed, 4 syntheses or guidelines pooled it, 108 citations in OpenAlex.
- Diagnostic accuracy of ultrasound models for assessment of ovarian tumors: systematic review and meta-analysis.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2026Pooled it
- Pooled it
- Menopausal status, ultrasound and biomarker tests in combination for the diagnosis of ovarian cancer in symptomatic women.The Cochrane database of systematic reviews · 2022Pooled it
- Diagnostic Accuracy of the ADNEX Model for Ovarian Cancer at the 15% Cut-Off Value: A Systematic Review and Meta-Analysis.Frontiers in oncology · 2021Pooled it
- Diagnostic significance of cancer antigen 125/carcinoembryonic antigen ratio combined with IOTA-ADNEX model in discriminating between primary ovarian cancer and ovarian metastases.Quantitative imaging in medicine and surgery · 2026Article
- Exploratory evaluation of a CEUS-derived substitution for solid-component measurement in the ADNEX model.BMC women's health · 2026Article
- Developing and validating ultrasound-based machine-learning models incorporating radiomics features to predict malignancy in adnexal masses.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2026Observational
- Ultrasound-based deep learning model as an assistant improves the diagnosis of ovarian tumors: a multicenter study.Insights into imaging · 2025Article
- Diagnostic Power of the Fibrinogen-to-Albumin Ratio for Estimating Malignancy in Patients with Adnexal Masses: A Methodological Study.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid morphology on ultrasound.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2025Observational
- Article
- Performance of International Ovarian Tumor Analysis (IOTA) predictive models in preoperative discrimination between benign and malignant adnexal lesions: preliminary outcomes in a Tertiary Care Hospital in Greece.Archives of gynecology and obstetrics · 2025Article
- Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study.Journal of ovarian research · 2024Article
- Review
- Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.BMC medical imaging · 2024Article
- Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery.British journal of cancer · 2024Article
- Machine learning and radiomics for segmentation and classification of adnexal masses on ultrasound.NPJ precision oncology · 2024Article
- Comparison of the value of the GI-RADS and ADNEX models in the diagnosis of adnexal tumors by junior physicians.Frontiers in oncology · 2024Article
- ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies.BMJ medicine · 2024Article
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7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesTo validate externally the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and compare this model with other frequently used models in the differentiation between benign and malignant adnexal masses.
methodsIn this retrospective diagnostic accuracy study, we assessed data collected prospectively from patients with adnexal pathology who underwent real-time transvaginal or transrectal ultrasound by a single expert ultrasonographer in a tertiary care hospital between July 2011 and July 2015. The presence of a malignancy was determined by subjective assessment and use of four prediction models: the ADNEX model, simple ultrasound-based rules (simple rules), Logistic Regression model 2 (LR2) and the Risk of Malignancy Index (RMI), of which three different variants were assessed. Pathology was the clinical reference standard.
resultsIn total, 851 consecutive patients underwent ultrasound examination for an adnexal mass. For 326 patients (128 premenopausal and 198 postmenopausal), pathology results were available (211 (64.7%) benign; 115 (35.3%) malignant) and these were included in the analysis. The area under the receiver-operating characteristics curve (AUC) of the ADNEX model for the discrimination between benign and malignant tumors was 0.93 (95% CI, 0.89-0.95). AUCs for the subtypes of malignancy (i.e. borderline, Stage I-IV and metastatic adnexal tumors) ranged between 0.60 and 0.90. Only subjective assessment (AUC, 0.96 (95% CI, 0.93-0.98)) was superior to the ADNEX model (P = 0.01) in differentiating malignant from benign tumors. AUCs for the other models were 0.92 (95% CI, 0.89-0.95) for LR2, 0.85 (95% CI, 0.81-0.89) for RMI-I, 0.82 (95% CI, 0.77-0.86) for RMI-II and 0.84 (95% CI, 0.80-0.88) for RMI-III. At the proposed cut-off of ≥ 10%, the ADNEX model had the highest sensitivity (0.98 (95% CI, 0.93-1.00)) but the lowest specificity (0.62 (95% CI, 0.55-0.68)) compared with the other models. Both subjective assessment (sensitivity, 0.90 (95% CI, 0.83-0.95); specificity 0.91 (95% CI, 0.86-0.94)) and the simple rules model with inconclusive cases classified by subjective assessment (sensitivity, 0.89 (95% CI, 0.81-0.94); specificity, 0.90 (95% CI, 0.85-0.94)) had lower sensitivity, but their sensitivity and specificity were better balanced.
conclusionsAlthough the test performance of subjective assessment by an expert remains superior, the ADNEX model can help in the differentiation between benign and malignant ovarian tumors. The advantage of the ADNEX model as a polytomous model remains to be shown. © 2016 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.
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