The role of prediction models in the classification of adnexal mass

Abstract

Prediction models play an important role in adnexal mass assessment since they allow clinicians to reliably differentiate adnexal mass as malignant or benign. The models use clinical and ultrasound features to generate a numerical score or probability of malignancy. The use of prediction models in adnexal mass assessment can have several benefits. For example, they can help clinicians identify patients at higher risk for malignancy and thus candidates for surgical treatment. They can also help to guide decision-making regarding the need for additional imaging and the extent of surgical procedures. One commonly used prediction model in adnexal mass assessment is the Risk of Malignancy Index (RMI), which incorporates menopausal status, ultrasound features of an adnexal mass, and serum levels of cancer antigen 125 to classify a lesion. The Simple Rules model is an easy and reproducible prediction model that uses selected (benign and malignant) ultrasound features to determine the likelihood of malignancy. Assessment of Different NEoplasias in the adneXa (ADNEX) model uses clinical and ultrasound features to calculate the probability of different types of malignancy. The malignancies are divided into border-line tumors, invasive ovarian cancer stage I, invasive ovarian cancer stage II - IV and secondary ovarian malignancies. This feature of the ADNEX model offers clinicians a more individualized approach to patients with an adnexal mass. In general, the use of predictive models in the evaluation of adnexal masses can be useful in daily clinical practice, but the decision on further diagnostic or therapeutic procedures should be made following the clinical context, respecting the wishes of the patient.