ArticleJournal of ovarian research2021
Estimating the risk of malignancy of adnexal masses: validation of the ADNEX model in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China.
Article in Journal of ovarian research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 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
- 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
- Investigation of multimodal deep learning models for predicting ovarian tumor malignancy based on ultrasound images and clinical information - a comprehensive comparative study against readers and O-RADS.BMC medical imaging · 2026Article
- Review
- Diagnostic value of magnetic resonance imaging for malignant ovarian tumors mis-subclassified by the ultrasound-based ADNEX model.Frontiers in oncology · 2025Article
- Article
- ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies.BMJ medicine · 2024Article
- Article
- Performance of IOTA Simple Rules Risks, ADNEX Model, Subjective Assessment Compared to CA125 and HE4 with ROMA Algorithm in Discriminating between Benign, Borderline and Stage I Malignant Adnexal Lesions.Diagnostics (Basel, Switzerland) · 2023Article
- Review
- Performance of the IOTA ADNEX model combined with HE4 for identifying early-stage ovarian cancer.Frontiers in oncology · 2022Article
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6 authors at 3 institutions in 1 country.
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Abstract
backgroundThis study aims to validate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) the Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China.
methodsThis was a single oncology centre, retrospective diagnostic accuracy study of 620 patients. All patients underwent surgery, and the histopathological diagnosis was used as a reference standard. The masses were divided into five types according to the ADNEX model: benign ovarian tumours, borderline ovarian tumours (BOTs), stage I ovarian cancer (OC), stage II-IV OC and ovarian metastasis. Receiver operating characteristic (ROC) curve analysis was used to evaluate the ability of the ADNEX model to classify tumours into different histological types with and without cancer antigen 125 (CA 125) results.
resultsOf the 620 women, 402 (64.8%) had a benign ovarian tumour and 218 (35.2%) had a malignant ovarian tumour, including 86 (13.9%) with BOT, 75 (12.1%) with stage I OC, 53 (8.5%) with stage II-IV OC and 4 (0.6%) with ovarian metastasis. The AUC of the model to differentiate benign and malignant adnexal masses was 0.97 (95% CI, 0.96-0.98). Performance was excellent for the discrimination between benign and stage II-IV OC and between benign and ovarian metastasis, with AUCs of 0.99 (95% CI, 0.99-1.00) and 0.99 (95% CI, 0.98-1.00), respectively. The model was less effective at distinguishing between BOT and stage I OC and between BOT and ovarian metastasis, with AUCs of 0.54 (95% CI, 0.45-0.64) and 0.66 (95% CI, 0.56-0.77), respectively. When including CA125 in the model, the performance in discriminating between stage II-IV OC and stage I OC and between stage II-IV OC ovarian metastasis was improved (AUC increased from 0.88 to 0.94, P = 0.01, and from 0.86 to 0.97, p = 0.01).
conclusionsThe IOTA ADNEX model has excellent performance in differentiating benign and malignant adnexal masses in the hands of nonexpert ultrasonographers with limited experience in China. In classifying different subtypes of ovarian cancers, the model has difficulty differentiating BOTs from stage I OC and BOTs from ovarian metastases.
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