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Objective: Previous work has suggested that the ultrasound-based benign simple descriptors (BDs) can reliably exclude malignancy in a large proportion of women presenting with an adnexal mass. This study aimed to validate a modified version of the BDs and to validate a two-step strategy to estimate the risk of malignancy, in which the modified BDs are followed by the Assessment of Different NEoplasias in the adneXa (ADNEX) model if modified BDs do not apply., Methods: This was a retrospective analysis using data from the 2-year interim analysis of the International Ovarian Tumor Analysis (IOTA) Phase-5 study, in which consecutive patients with at least one adnexal mass were recruited irrespective of subsequent management (conservative or surgery). The main outcome was classification of tumors as benign or malignant, based on histology or on clinical and ultrasound information during 1 year of follow-up. Multiple imputation was used when outcome based on follow-up was uncertain according to predefined criteria., Results: A total of 8519 patients were recruited at 36 centers between 2012 and 2015. We excluded patients who were already in follow-up at recruitment and all patients from 19 centers that did not fulfil our criteria for good-quality surgical and follow-up data, leaving 4905 patients across 17 centers for statistical analysis. Overall, 3441 (70%) tumors were benign, 978 (20%) malignant and 486 (10%) uncertain. The modified BDs were applicable in 1798/4905 (37%) tumors, of which 1786 (99.3%) were benign. The two-step strategy based on ADNEX without CA125 had an area under the receiver-operating-characteristics curve (AUC) of 0.94 (95% CI, 0.92-0.96). The risk of malignancy was slightly underestimated, but calibration varied between centers. A sensitivity analysis in which we expanded the definition of uncertain outcome resulted in 1419 (29%) tumors with uncertain outcome and an AUC of the two-step strategy without CA125 of 0.93 (95% CI, 0.91-0.95)., Conclusion: A large proportion of adnexal masses can be classified as benign by the modified BDs. For the remaining masses, the ADNEX model can be used to estimate the risk of malignancy. This two-step strategy is convenient for clinical use. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology., (© 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.)

Objectives: To assess whether vessel morphology depicted by three-dimensional (3D) power Doppler ultrasound improves discrimination between benignity and malignancy if used as a second-stage test in adnexal masses that are difficult to classify., Methods: This was a prospective observational international multicenter diagnostic accuracy study. Consecutive patients with an adnexal mass underwent standardized transvaginal two-dimensional (2D) grayscale and color or power Doppler and 3D power Doppler ultrasound examination by an experienced examiner, and those with a 'difficult' tumor were included in the current analysis. A difficult tumor was defined as one in which the International Ovarian Tumor Analysis (IOTA) logistic regression model-1 (LR-1) yielded an ambiguous result (risk of malignancy, 8.3% to 25.5%), or as one in which the ultrasound examiner was uncertain regarding classification as benign or malignant when using subjective assessment. Even when the ultrasound examiner was uncertain, he/she was obliged to classify the tumor as most probably benign or most probably malignant. For each difficult tumor, one researcher created a 360° rotating 3D power Doppler image of the vessel tree in the whole tumor and another of the vessel tree in a 5-cm 3 spherical volume selected from the most vascularized part of the tumor. Two other researchers, blinded to the patient's history, 2D ultrasound findings and histological diagnosis, independently described the vessel tree using predetermined vessel features. Their agreed classification was used. The reference standard was the histological diagnosis of the mass. The sensitivity of each test for discriminating between benign and malignant difficult tumors was plotted against 1 - specificity on a receiver-operating-characteristics diagram, and the test with the point furthest from the reference line was considered to have the best diagnostic ability., Results: Of 2403 women with an adnexal mass, 376 (16%) had a difficult mass. Ultrasound volumes were available for 138 of these cases. In 79/138 masses, the ultrasound examiner was uncertain about the diagnosis based on subjective assessment, in 87/138, IOTA LR-1 yielded an ambiguous result and, in 28/138, both methods gave an uncertain result. Of the masses, 38/138 (28%) were malignant. Among tumors that were difficult to classify as benign or malignant by subjective assessment, the vessel feature 'densely packed vessels' had the best discriminative ability (sensitivity 67% (18/27), specificity 83% (43/52)) and was slightly superior to subjective assessment (sensitivity 74% (20/27), specificity 60% (31/52)). In tumors in which IOTA LR-1 yielded an ambiguous result, subjective assessment (sensitivity 82% (14/17), specificity 79% (55/70)) was superior to the best vascular feature, i.e. changes in the diameter of vessels in the whole tumor volume (sensitivity 71% (12/17), specificity 69% (48/70))., Conclusion: Vessel morphology depicted by 3D power Doppler ultrasound may slightly improve discrimination between benign and malignant adnexal tumors that are difficult to classify by subjective ultrasound assessment. For tumors in which the IOTA LR-1 model yields an ambiguous result, subjective assessment is superior to vessel morphology as a second-stage test. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology., (© 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.)

Background: Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant., Objective: We sought 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: This was an 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 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 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 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (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 area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (<1%) and 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., (Copyright © 2016 Elsevier Inc. All rights reserved.)

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., (© Van Calster et al 2014.)

Objectives: To develop a logistic regression model for discrimination between benign and malignant unilocular solid cysts with papillary projections but no other solid components, and to compare its diagnostic performance with that of subjective evaluation of ultrasound findings (subjective assessment), CA  125 and the risk of malignancy index (RMI)., Methods: Among the 3511 adnexal masses in the International Ovarian Tumor Analysis (IOTA) database there were 252 (7%) unilocular solid cysts with papillary projections but no other solid components ('unilocular cysts with papillations'). All had been examined with transvaginal ultrasound using the IOTA standardized research protocol. The ultrasound examiner had also classified each mass as certainly or probably benign, unclassifiable, or certainly or probably malignant. A logistic regression model to discriminate between benignity and malignancy was developed for all unilocular cysts with papillations (175 tumors in the training set and 77 in the test set) and for unilocular cysts with papillations for which the ultrasound examiner was not certain about benignity/malignancy (113 tumors in the training set and 53 in the test set). The gold standard was the histological diagnosis of the surgically removed adnexal mass., Results: A model containing six variables was developed for all unilocular cysts with papillations. The model had an area under the receiver-operating characteristics curve (AUC) on the test set of 0.83 (95% CI, 0.74-0.93). The optimal risk cut-off, as defined on the training set (0.35), resulted in sensitivity 69% (20/29), specificity 79% (38/48), positive likelihood ratio (LR +) 3.31 and negative likelihood ratio (LR-) 0.39 on the test set. The corresponding values for subjective assessment when using the ultrasound examiner's dichotomous classification of the mass as benign or malignant were 97% (28/29), 79% (38/48), 4.63 and 0.04. A model containing four variables was developed for unilocular cysts with papillations for which the ultrasound examiner was not certain about benignity/malignancy. The model had an AUC of 0.74 (95% CI, 0.60-0.88) on the test set. The optimal risk cut-off of the model, as defined on the training set (0.30), resulted in sensitivity 57% (12/21), specificity 78% (25/32), LR + 2.61 and LR- 0.55 on the test set. The corresponding values for subjective assessment were 95% (20/21), 78% (25/32), 4.35 and 0.06. CA  125 and RMI had virtually no diagnostic ability., Conclusions: Even though logistic regression models to predict malignancy in unilocular cysts with papillations can be developed, they have at most moderate performance and are not superior to subjective assessment for discrimination between benignity and malignancy., (Copyright © 2012 ISUOG. Published by John Wiley & Sons Ltd.)

Objectives: 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)., Methods: We used a multicenter IOTA database of 2445 patients with at least one adnexal mass, i.e. the database previously used to prospectively validate the diagnostic performance of LR1 and LR2. The masses were categorized into three subgroups according to their largest diameter: small tumors (diameter < 4 cm; n = 396), medium-sized tumors (diameter, 4-9.9 cm; n = 1457) and large tumors (diameter ≥ 10 cm, n = 592). Subjective assessment, LR1 and LR2, IOTA simple rules and the RMI were applied to each of the three groups. Sensitivity, specificity, positive and negative likelihood ratio (LR+, LR-), diagnostic odds ratio (DOR) and area under the receiver-operating characteristics curve (AUC) were used to describe diagnostic performance. A moving window technique was applied to estimate the effect of tumor size as a continuous variable on the AUC. The reference standard was the histological diagnosis of the surgically removed adnexal mass., Results: The frequency of invasive malignancy was 10% in small tumors, 19% in medium-sized tumors and 40% in large tumors; 11% of the large tumors were borderline tumors vs 3% and 4%, respectively, of the small and medium-sized tumors. The type of benign histology also differed among the three subgroups. For all methods, sensitivity with regard to malignancy was lowest in small tumors (56-84% vs 67-93% in medium-sized tumors and 74-95% in large tumors) while specificity was lowest in large tumors (60-87%vs 83-95% in medium-sized tumors and 83-96% in small tumors ). The DOR and the AUC value were highest in medium-sized tumors and the AUC was largest in tumors with a largest diameter of 7-11 cm., Conclusion: Tumor size affects the performance of subjective assessment, LR1 and LR2, the IOTA simple rules and the RMI in discriminating correctly between benign and malignant adnexal masses. The likely explanation, at least in part, is the difference in histology among tumors of different size., (Copyright © 2012 ISUOG. Published by John Wiley & Sons, Ltd.)

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.

Objective: 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)., Methods: We used data from the 3511 patients with an adnexal mass included in the International Ovarian Tumor Analysis (IOTA) studies. All patients had been examined using transvaginal gray-scale and Doppler ultrasound following a standardized research protocol carried out by an experienced ultrasound examiner using a high-end ultrasound system. In addition to prospectively collecting information on > 40 clinical and ultrasound variables, the ultrasound examiner classified each mass as certainly or probably benign, unclassifiable, or certainly or probably malignant. A logistic regression model to discriminate between benignity and malignancy was developed for the unclassifiable masses (n = 244, i.e. 7% of all tumors) using a training set (160 tumors, 45 malignancies) and then tested on a test set (84 tumors, 28 malignancies). The gold standard was the histological diagnosis of the surgically removed adnexal mass. The area under the receiver-operating characteristics curve (AUC), sensitivity, specificity, positive likelihood ratio (LR+) and negative likelihood ratio (LR-) were used to describe diagnostic performance and were compared between subjective assessment, CA 125, the RMI and the logistic regression model created., Results: One variable was retained in the logistic regression model: the largest diameter (in mm) of the largest solid component of the tumor (odds ratio (OR) = 1.04; 95% CI, 1.02-1.06). The model had an AUC of 0.68 (95% CI, 0.59-0.78) on the training set and an AUC of 0.65 (95% CI, 0.53-0.78) on the test set. On the test set, a cut-off of 25% probability of malignancy (corresponding to the largest diameter of the largest solid component of 23 mm) resulted in a sensitivity of 64% (18/28), a specificity of 55% (31/56), an LR+ of 1.44 and an LR- of 0.65. The corresponding values for subjective assessment were 68% (19/28), 59% (33/56), 1.65 and 0.55. On the test set of patients with available CA 125 results, the LR+ and LR- of the logistic regression model (cut-off = 25% probability of malignancy) were 1.29 and 0.73, of subjective assessment were 1.45 and 0.63, of CA 125 (cut-off = 35 U/mL) were 1.24 and 0.84 and of RMI (cut-off = 200) were 1.21 and 0.92., Conclusions: About 7% of adnexal masses that are considered appropriate for surgical removal cannot be classified as benign or malignant by experienced ultrasound examiners using subjective assessment. Logistic regression models to estimate the risk of malignancy, CA 125 measurements and the RMI are not helpful in these masses., (Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.)

Objective: Two logistic regression models have been developed for the characterization of adnexal masses. The goal of this prospective analysis was to see whether these models perform differently according to the prevalence of malignancy and whether the cut-off levels of risk assessment for malignancy by the models require modification in different centers., Methods: Centers were categorized into those with a prevalence of malignancy below 15%, between 15 and 30% and above 30%. The areas under the receiver-operating characteristics curves (AUC) were compared using bootstrapping. The optimal cut-off level of risk assessment for malignancy was chosen per center, corresponding to the highest sensitivity level possible while still keeping a good specificity., Results: Both models performed better in centers with a lower prevalence of malignant cases. The AUCs of the two models for centers with fewer than 15% malignant cases were 0.97 and 0.95, those of centers with 15-30% malignancy were 0.95 and 0.93 and those of centers with more than 30% malignant cases were 0.94 and 0.92. This decrease in performance was due mainly to the decrease in specificity from over 90 to around 76%. In the centers with a higher percentage of malignant cases, a sensitivity of at least 90% with a good specificity could not be obtained by choosing a different cut-off level., Conclusions: Overall the models performed well in all centers. The performance of the logistic regression models worsened with increasing prevalence of malignancy, due to a case mix with more borderline and complex benign masses seen in those centers. Because the cut-off of 0.10 is optimal for all three types of center, it seems reasonable to use this cut-off for both models in all centers., (Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.)

Objective: 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., Methods: The diagnostic performance with regard to discrimination between benign and malignant adnexal masses for mathematical models including ultrasound variables and for subjective evaluation of ultrasound findings by an experienced ultrasound examiner was expressed as area under the receiver-operating characteristics curve (AUC), sensitivity and specificity. These were calculated for the total study population of 1938 patients with an adnexal mass as well as for subpopulations defined by the certainty with which the diagnosis of benignity or malignancy was made. The effect of applying a second-stage test to the tumors where risk estimation was uncertain was determined., Results: The best mathematical model (LR1) had an AUC of 0.95, sensitivity of 92% and specificity of 84% when applied to all tumors. When model LR1 was applied to the 10% of tumors in which the calculated risk fell closest to the risk cut-off of the model, the AUC was 0.59, sensitivity 90% and specificity 21%. A strategy where subjective evaluation was used to classify these 10% of tumors for which LR1 performed poorly and where LR1 was used in the other 90% of tumors resulted in a sensitivity of 91% and specificity of 90%. Applying subjective evaluation to all tumors yielded an AUC of 0.95, sensitivity of 90% and specificity of 93%. Sensitivity was 81% and specificity 47% for those patients where the ultrasound examiner was uncertain about the diagnosis (n = 115; 5.9%). No mathematical model performed better than did subjective evaluation among the 115 tumors where the ultrasound examiner was uncertain., Conclusion: When model LR1 is used as a primary test for discriminating between benign and malignant adnexal masses, the use of subjective evaluation of ultrasound findings by an experienced examiner as a second-stage test in the 10% of cases for which the model yields a risk of malignancy closest to its risk cut-off will improve specificity without substantially decreasing sensitivity. However, none of the models tested proved suitable as a second-stage test in tumors where subjective evaluation yielded an uncertain result.

Objective: To determine the ability of acoustic streaming to discriminate between endometriomas and other adnexal masses., Methods: We used data from 1938 patients with an adnexal mass included in Phase 2 of the International Ovarian Tumor Analysis (IOTA) study. All patients had been examined by transvaginal gray-scale and Doppler ultrasound following a standardized research protocol. Assessment of acoustic streaming was voluntary and was carried out only in lesions containing echogenic cyst fluid. Acoustic streaming was defined as movement of particles inside the cyst fluid during gray-scale and/or color Doppler examination provided that the probe had been held still for two seconds to ensure that the movement of the particles was not caused by movement of the probe or the patient. Only centers where acoustic streaming had been evaluated in > 90% of cases were included. Sensitivity, specificity, positive and negative likelihood ratios (LR+, LR-), and positive and negative predictive values (PPV and NPV) of acoustic streaming with regard to endometrioma were calculated., Results: 460 (24%) masses were excluded because they were examined in centers where

We have attempted to determine the accuracy of greyscale and color Doppler ultrasound in the differentiation of adnexal masses in pregnancy. The studied group included 2245 pregnant women from low risk population. Following criteria were evaluated: maximal diameter and volume of the tumor, echogenicity, presence of septa and papillary projections in grey scale sonography. Color Doppler analysis included blood vessel presence and arrangement and blood flow characteristics with the use of pulsatility (PI), resistive (RI) and systolic/diastolic (S/D) indices. Preoperative CA-125 serum levels were available in 11 patients. In 66 (2.94%) patients adnexal tumors were detected during routine ultrasound scan at the end of the first trimester. Twenty-seven masses (1.2%) persisted beyond 16 weeks of gestation and were subsequently surgically removed. Pathological diagnosis confirmed 19 serous cystadenomas, 4 endometriomas and 2 dermoids, one pedunculated myoma and one fibrothecoma. Mean size of the tumors was 79 Jmm (range: 43-245 mm), mean volume 166. lml (range: 30-1320 ml). Doppler indices values presented as mean, SD and range were as follows: PI = 1.26 +/- 0.71 (range: 0.57-3.84); RI = 0.61 +/- 0.15 (range: 0.33-0.89) and S/D = 2.62 +/- 0.98 (range: 1.17-4.91). Median serum concentration of CA-125 was 17 IU/ml (range: 8.4-1247 IU/ml). Only 3 of these women had elevated (> 35 IU/ml) levels: 2 endometriomas (344 IU/ml and 1247 IU/ml) and one myoma (37 IU/ml), respectively. Based on the sonographic findings two solid tumors were incorrectly classified as probably malignant (fibrothecoma and subserous myoma). Negative predictive value of ultrasound diagnosis in the studied population was therefore 92.6% (25 of 27). We conclude that although prenatal sonography has the potential to correctly classify most of adnexal masses, caution in risk assessment is needed especially when persistent solid tumor is found.

BACKGROUND: Borderline ovarian tumors (BOTs) and early clinical stage malignant adnexal masses can make sonographic diagnosis challenging, while the clinical utility of tumor markers, e.g., CA125 and HE4, or the ROMA algorithm, remains controversial in such cases. OBJECTIVE: To compare the IOTA group Simple Rules Risk (SRR), the ADNEX model and the subjective assessment (SA) with serum CA125, HE4 and the ROMA algorithm in the preoperative discrimination between benign tumors, BOTs and stage I malignant ovarian lesions (MOLs). METHODS: A multicenter retrospective study was conducted with lesions classified prospectively using subjective assessment and tumor markers with the ROMA. The SRR assessment and ADNEX risk estimation were applied retrospectively. The sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR−) were calculated for all tests. RESULTS: In total, 108 patients (the median age: 48 yrs, 44 postmenopausal) with 62 (79.6%) benign masses, 26 (24.1%) BOTs and 20 (18.5%) stage I MOLs were included. When comparing benign masses with combined BOTs and stage I MOLs, SA correctly identified 76% of benign masses, 69% of BOTs and 80% of stage I MOLs. Significant differences were found for the presence and size of the largest solid component (p = 0.0006), the number of papillary projections (p = 0.01), papillation contour (p = 0.008) and IOTA color score (p = 0.0009). The SRR and ADNEX models were characterized by the highest sensitivity (80% and 70%, respectively), whereas the highest specificity was found for SA (94%). The corresponding likelihood ratios were as follows: LR+ = 3.59 and LR− = 0.43 for the ADNEX; LR+ = 6.40 and LR− = 0.63 for SA and LR+ = 1.85 with LR− = 0.35 for the SRR. The sensitivity and specificity of the ROMA test were 50% and 85%, respectively, with LR+ = 3.44 and LR− = 0.58. Of all the tests, the ADNEX model had the highest diagnostic accuracy of 76%. CONCLUSIONS: This study demonstrates the limited value of diagnostics based on CA125 and HE4 serum tumor markers and the ROMA algorithm as independent modalities for the detection of BOTs and early stage adnexal malignant tumors in women. SA and IOTA methods based on ultrasound examination may present superior value over tumor marker assessment. [ABSTRACT FROM AUTHOR]

Background: To evaluate the accuracy of subjective assessment (SA), the International Ovarian Tumor Analysis (IOTA) group Simple Rules Risk (SRR) and the Assessment of Different NEoplasias in the adneXa (ADNEX) model for the preoperative differentiation of adnexal masses in pregnant women. Methods: The study population comprised 36 pregnant women (median age: 28.5 years old, range: 20–42 years old) with a mean gestation age of 13.5 (range: 8–31) weeks at diagnosis. Tumors were prospectively classified by local sonographers as probably benign or probably malignant using SA. Final tumor histological diagnosis was used as the reference standard in all cases. Logistic regression SRR and ADNEX models were used to obtain a risk score for every case. Serum CA125 and human epidydimis protein 4 (HE4) concentrations were also retrieved and the Risk of Ovarian Malignancy Algorithm (ROMA) value was calculated. The calculated predictive values included positive and negative likelihood ratios of ultrasound and biochemical tests. Results: Final histology confirmed 27 benign and 9 malignant (including 2 borderline) masses. The highest sensitivity (89%) and specificity (70%) were found for the subjective tumor assessment. Although no malignancy was classified as benign using the SRR criteria (sensitivity = 100%), the specificity of this scoring system was only 37%. At the cut-off risk level of >20%, the ADNEX model had a sensitivity of 78% and a specificity of 70%. Serum levels of CA125, HE4 and the ROMA risk model correctly identified adnexal malignant tumors with a sensitivity of 67%, 25% and 25%, respectively. Corresponding specificities were 72%, 100% and 100%, respectively. The highest positive and negative likelihood ratios were found for SA (LR+ = 3.0 and LR− = 0.16, respectively). Overall diagnostic accuracy of all predictive methods used in this study were similar (range: 70–75%) except for SRR (53%). Conclusion: Subjective assessment remains the best predictive method in complex adnexal masses found at prenatal ultrasound in pregnant women. For less experienced sonographers, both the SRR and ADNEX scoring systems may be also used for the characterization of such tumors, while serum tumor markers CA125 and HE4, along with the ROMA algorithm appear to be less accurate. [ABSTRACT FROM AUTHOR]

An abstract of the article "Prospective validation of the ADNEX model without CA-125 in the differentiation between benign and malignant adnexal masses," by W. Froyman and colleagues is presented.

An abstract of the article "Two-step strategy to preoperatively assess adnexal lesions not classifiable by EDs, using RMI, IOTA ADNEX or simple rules risk model," by C. Landolfo and colleagues is presented.

An abstract of the conference paper "Confirming the limited role of CA-125 for adnexal mass diagnosis," by B. Van Calster and colleagues is presented.

An abstract of a research paper related to logistic regression model and risk of malignancy (RMI) model in preoperative adnexal masses by A. Czekierdowski and colleagues is presented.

An abstract of the conference paper "Which histologies limit the ability of CA-125 to characterize adnexal masses? An observational study of 3511 patients," by B. Van Calster and colleagues is presented.

An abstract of the conference paper "Unilocular solid adnexal masses with papillary projections but no other solid components: is there a logistic regression model that can help?," by L. I. Valentin, and colleagues is presented.

An abstract of the conference paper "Adnexal masses difficult to classify as benign or malignant using subjective evaluation of ultrasound findings: logistic regression models do not help," by L. Ameye, and colleagues is presented.

An abstract of the conference paper "Multivariate Adaptive Regression Splines (MARS) statistical modeling of clinical and sonographic data for the preoperative classification of adnexal tumors," by A. Smolen and colleagues is presented.

An abstract of the conference paper "Presence of acoustic streaming in different types of adnexal masses," by C. Van Holsbeke, and colleagues is presented.

An abstract of the conference paper "Prospective external validation of an ultrasound scoring system to differentiate benign from malignant masses in specific subgroups of adnexal tumors," by L. Valentin and colleagues is presented.

An abstract of the conference paper "Prospective assessment of simple rules to distinguish between malignant and benign adnexal masses prior to surgery," by D. Timmerman and colleagues is presented.

An abstract of the article "Multicenter prospective testing to predict malignancy in adnexal masses using Bayesian network models," by O. Gevaert and colleagues, is presented.