A. Czekierdowski

Ovarian cancer prediction in adnexal masses using ultrasound‐based logistic regression models: a temporal and external validation study by the IOTA group

The aims of the study were to temporally and externally validate the diagnostic performance of two logistic regression models containing clinical and ultrasound variables in order to estimate the risk of malignancy in adnexal masses, and to compare the results with the subjective interpretation of ultrasound findings carried out by an experienced ultrasound examiner (‘subjective assessment’).

Endometriomas: their ultrasound characteristics

To describe the ultrasound characteristics of endometriomas in pre‐ and postmenopausal patients and to develop rules that characterize endometriomas.

Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study.

Objectives To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours. Design Observational diagnostic study using prospectively collected clinical and ultrasound data. Setting 24 ultrasound centres in 10 countries. Participants Women with an ovarian (including para-ovarian and tubal) mass and who underwent a standardised ultrasound examination before surgery. The model was developed on 3506 patients recruited between 1999 and 2007, temporally validated on 2403 patients recruited between 2009 and 2012, and then updated on all 5909 patients. Main outcome measures Histological classification and surgical staging of the mass. Results The Assessment of Different NEoplasias in the adneXa (ADNEX) model contains three clinical and six ultrasound predictors: age, serum CA-125 level, type of centre (oncology centres v other hospitals), maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. The area under the receiver operating characteristic curve (AUC) for the classic discrimination between benign and malignant tumours was 0.94 (0.93 to 0.95) on temporal validation. The AUC was 0.85 for benign versus borderline, 0.92 for benign versus stage I cancer, 0.99 for benign versus stage II-IV cancer, and 0.95 for benign versus secondary metastatic. AUCs between malignant subtypes varied between 0.71 and 0.95, with an AUC of 0.75 for borderline versus stage I cancer and 0.82 for stage II-IV versus secondary metastatic. Calibration curves showed that the estimated risks were accurate. Conclusions The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy. The use of ADNEX has the potential to improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.

External validation of diagnostic models to estimate the risk of malignancy in adnexal masses

Purpose: To externally validate and compare the performance of previously published diagnostic models developed to predict malignancy in adnexal masses. Experimental Design: 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−). Results: 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. Conclusion: External validation shows that the IOTA models outperform other models, including the current reference test RMI, for discriminating between benign and malignant adnexal masses. Clin Cancer Res; 18(3); 815–25. ©2011 AACR.

Adnexal masses difficult to classify as benign or malignant using subjective assessment of gray‐scale and Doppler ultrasound findings: logistic regression models do not help

To develop a logistic regression model that can discriminate between benign and malignant adnexal masses perceived to be difficult to classify by subjective evaluation of gray‐scale and Doppler ultrasound findings (subjective assessment) and to compare its diagnostic performance with that of subjective assessment, serum CA 125 and the risk of malignancy index (RMI).

Strategies to diagnose ovarian cancer: new evidence from phase 3 of the multicentre international IOTA study

Background:To compare different ultrasound-based international ovarian tumour analysis (IOTA) strategies and risk of malignancy index (RMI) for ovarian cancer diagnosis using a meta-analysis approach of centre-specific data from IOTA3.Methods:This prospective multicentre diagnostic accuracy study included 2403 patients with 1423 benign and 980 malignant adnexal masses from 2009 until 2012. All patients underwent standardised transvaginal ultrasonography. Test performance of RMI, subjective assessment (SA) of ultrasound findings, two IOTA risk models (LR1 and LR2), and strategies involving combinations of IOTA simple rules (SRs), simple descriptors (SDs) and LR2 with and without SA was estimated using a meta-analysis approach. Reference standard was histology after surgery.Results:The areas under the receiver operator characteristic curves of LR1, LR2, SA and RMI were 0.930 (0.917–0.942), 0.918 (0.905–0.930), 0.914 (0.886–0.936) and 0.875 (0.853–0.894). Diagnostic one-step and two-step strategies using LR1, LR2, SR and SD achieved summary estimates for sensitivity 90–96%, specificity 74–79% and diagnostic odds ratio (DOR) 32.8–50.5. Adding SA when IOTA methods yielded equivocal results improved performance (DOR 57.6–75.7). Risk of Malignancy Index had sensitivity 67%, specificity 91% and DOR 17.5.Conclusions:This study shows all IOTA strategies had excellent diagnostic performance in comparison with RMI. The IOTA strategy chosen may be determined by clinical preference.

A Novel Approach to Predict the Likelihood of Specific Ovarian Tumor Pathology Based on Serum CA-125: A Multicenter Observational Study.

Background: The CA-125 tumor marker has limitations when used to distinguish between benign and malignant ovarian masses. We therefore establish likelihood curves of six subgroups of ovarian pathology based on CA-125 and menopausal status. Methods: This cross-sectional study conducted by the International Ovarian Tumor Analysis group involved 3,511 patients presenting with a persistent adnexal mass that underwent surgical intervention. CA-125 distributions for six tumor subgroups (endometriomas and abscesses, other benign tumors, borderline tumors, stage I invasive cancers, stage II–IV invasive cancers, and metastatic tumors) were estimated using kernel density estimation with stratification for menopausal status. Likelihood curves for the tumor subgroups were derived from the distributions. Results: Endometriomas and abscesses were the only benign pathologies with median CA-125 levels above 20 U/mL (43 and 45, respectively). Borderline and invasive stage I tumors had relatively low median CA-125 levels (29 and 81 U/mL, respectively). The CA-125 distributions of stage II–IV invasive cancers and benign tumors other than endometriomas or abscesses were well separated; the distributions of the other subgroups overlapped substantially. This held for premenopausal and postmenopausal patients. Likelihood curves and reference tables comprehensibly show how subgroup likelihoods change with CA-125 and menopausal status. Conclusions and Impact: Our results confirm the limited clinical value of CA-125 for preoperative discrimination between benign and malignant ovarian pathology. We have shown that CA-125 may be used in a different way. By using likelihood reference tables, we believe clinicians will be better able to interpret preoperative serum CA-125 results in patients with adnexal masses. Cancer Epidemiol Biomarkers Prev; 20(11); 2420–8. ©2011 AACR.

Acoustic streaming cannot discriminate reliably between endometriomas and other types of adnexal lesion: a multicenter study of 633 adnexal masses

To determine the ability of acoustic streaming to discriminate between endometriomas and other adnexal masses.

Improving the preoperative classification of adnexal masses as benign or malignant by second stage tests

The aim of this study was to establish when a second‐stage diagnostic test may be of value in cases where a primary diagnostic test has given an uncertain diagnosis of the benign or malignant nature of an adnexal mass.

Lesion size affects diagnostic performance of IOTA logistic regression models, IOTA simple rules and risk of malignancy index in discriminating between benign and malignant adnexal masses

To estimate the ability to discriminate between benign and malignant adnexal masses of different size using: subjective assessment, two International Ovarian Tumor Analysis (IOTA) logistic regression models (LR1 and LR2), the IOTA simple rules and the risk of malignancy index (RMI).