External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses

Caroline Van Holsbeke,Luca Savelli,Silvia Ajossa,Tom Bourne,Robert Fruscio,Dirk Timmerman,Sabine Van Huffel,Stefano Guerriero,Andrea Alberto Lissoni,Lil Valentin,Antonia C Testa,Ben Van Calster,Artur Czekierdowski

doi:10.1158/1078-0432.ccr-11-0879

Abstract

To externally validate and compare the performance of previously published diagnostic models developed to predict malignancy in adnexal masses. We externally validated the diagnostic performance of 11 models developed by the International Ovarian Tumor Analysis (IOTA) group and 12 other (non-IOTA) models on 997 prospectively collected patients. The non-IOTA models included the original risk of malignancy index (RMI), three modified versions of the RMI, six logistic regression models, and two artificial neural networks. The ability of the models to discriminate between benign and malignant adnexal masses was expressed as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and likelihood ratios (LR(+), LR(-)). Seven hundred and forty-two (74%) benign and 255 (26%) malignant masses were included. The IOTA models did better than the non-IOTA models (AUCs between 0.941 and 0.956 vs. 0.839 and 0.928). The difference in AUC between the best IOTA and the best non-IOTA model was 0.028 [95% confidence interval (CI), 0.011-0.044]. The AUC of the RMI was 0.911 (difference with the best IOTA model, 0.044; 95% CI, 0.024-0.064). The superior performance of the IOTA models was most pronounced in premenopausal patients but was also observed in postmenopausal patients. IOTA models were better able to detect stage I ovarian cancer. External validation shows that the IOTA models outperform other models, including the current reference test RMI, for discriminating between benign and malignant adnexal masses.

Highlights

The most important role of the sonologist examining patients with an adnexal mass is to distinguish between benign and malignant masses to optimally triage patients
External validation shows that the International Ovarian Tumor Analysis (IOTA) models outperform other models, including the current reference test risk of malignancy index (RMI), for discriminating between benign and malignant adnexal masses
The non-IOTA models From a literature search, we identified 12 models to estimate the risk of malignancy in adnexal masses that contained variables for which information had been prospectively collected in the IOTA studies: the original RMI from the study of Jacobs and colleagues [7] and 3 variations of the RMI [8, 28, 29], 6 logistic regression models [9,10,11,12,13,14], and 2 ANNs

Summary

Introduction

The most important role of the sonologist examining patients with an adnexal mass is to distinguish between benign and malignant masses to optimally triage patients. Benign masses can be managed conservatively or—if technically feasible—be removed by laparoscopy. Patients with masses that are presumed to be malignant should be referred to gynecologic oncologists for proper staging and debulking [1,2,3]. The sonologist can use different strategies to assess the risk of malignancy but there is still no consensus as to the optimal approach. Subjective assessment of the sonographic characteristics of the mass is an excellent method to discriminate between benign and malignant but only in the hands of experienced ultrasound examiners [4, 5]

Methods

Results

Discussion

Conclusion