Authors: Dirk Timmerman, Ben Van Calster, Antonia Testa, Luca Savelli, Daniela Fischerova, Wouter Froyman, Laure Wynants, Caroline Van Holsbeke, Elisabeth Epstein, Dorella Franchi, Jeroen Kaijser, Artur Czekierdowksi, Stefano Guerriero, Robert Fruscio, Francesco PG. Leone, Alberto Rossi, Chiara Landolfo, Ignace Vergote, Tom Bourne, Lil Valentin
Summary:
Background: Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent meta-analysis concluded that the International Ovarian Tumor Analysis (IOTA) algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant.
Objective: To develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules.
Study Design: International cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in three phases between 2002 and 2012. The five Simple Rules features indicative of a benign tumor (B-features) and the five features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the ten ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive and negative likelihood ratios (LR+, LR-), positive and negative predictive values (PPV, NPV) and calibration curves.
Results: Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The AUC on validation data was very similar in oncology centers (0.917, 95% CI 0.901 to 0.931) and other centers (0.916, 95% CI 0.873 to 0.945). Risk estimates showed good calibration. 23% of patients in the validation data set had a very low estimated risk (<1%), 48% had a high estimated risk (≥30%). For the 1% risk cutoff, sensitivity was 99.7%, specificity 33.7%, LR+ 1.5, LR- 0.010, PPV 44.8% and NPV 98.9%. For the 30% risk cutoff, sensitivity was 89.0%, specificity 84.7%, LR+ 5.8, LR- 0.13, PPV 75.4% and NPV 93.9%.
Conclusion: Quantification of the risk of malignancy based on the Simple Rules has good diagnostic performance both in oncology centers and other centers. A simple classification based on these risk estimates may form the basis of a clinical management system. Patients with a high risk may benefit from surgery by a gynecological oncologist, while patients with a lower risk may be managed locally.
Source:
American Journal of Obstetrics and Gynecology, 2016