Background:The International Ovarian Tumour Analysis (IOTA) group have developed the ADNEX (The Assessment of Different NEoplasias in the adneXa) model to predict the risk that an ovarian mass is benign, borderline, stage I, stages II–IV or metastatic. We aimed to externally validate the ADNEX model in the hands of examiners with varied training and experience.Methods:This was a multicentre cross-sectional cohort study for diagnostic accuracy. Patients were recruited from three cancer centres in Europe. Patients who underwent transvaginal ultrasonography and had a histological diagnosis of surgically removed tissue were included. The diagnostic performance of the ADNEX model with and without the use of CA125 as a predictor was calculated.Results:Data from 610 women were analysed. The overall prevalence of malignancy was 30%. The area under the receiver operator curve (AUC) for the ADNEX diagnostic performance to differentiate between benign and malignant masses was 0.937 (95% CI: 0.915–0.954) when CA125 was included, and 0.925 (95% CI: 0.902–0.943) when CA125 was excluded. The calibration plots suggest good correspondence between the total predicted risk of malignancy and the observed proportion of malignancies. The model showed good discrimination between the different subtypes.Conclusions:The performance of the ADNEX model retains its performance on external validation in the hands of ultrasound examiners with varied training and experience.
Characterizing ovarian masses enables patients with malignancy to be appropriately triaged for treatment by subspecialist gynecological oncologists, which has been shown to optimize care and improve survival. Furthermore, correctly classifying benign masses facilitates the selection of patients with ovarian pathology that may either not require intervention, or be suitable for minimal access surgery if intervention is required. However, predicting whether a mass is benign or malignant is not the only clinically relevant information that we need to know before deciding on appropriate treatment. Knowing the specific histology of a mass is becoming of increasing importance as management options become more tailored to the individual patient. For example predicting a mucinous borderline tumor gives the opportunity for fertility sparing surgery, and will highlight the need for further gastrointestinal assessment. For benign disease, predicting the presence of an endometrioma and possible deeply infiltrating endometriosis is important when considering both who should perform and the extent of surgery. An examiner’s subjective assessment of the morphological and vascular features of a mass using ultrasonography has been shown to be highly effective for predicting whether a mass is benign or malignant. Many masses also have features that enable a reliable diagnosis of the specific pathology of a particular mass to be made. In this narrative review we aim to describe the typical morphological features seen on ultrasound of different adnexal masses and illustrate these by showing representative ultrasound images.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.