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Background: Multiple risk-prediction models are used in clinical practice to triage patients as being at low risk or high risk of ovarian cancer. In the ROCkeTS study, we aimed to identify the best diagnostic test for ovarian cancer in symptomatic patients, through head-to-head comparisons of risk-prediction models, in a real-world setting. Here, we report the results for the postmenopausal cohort., Methods: In this multicentre, prospective diagnostic accuracy study, we recruited newly presenting female patients aged 16-90 years with non-specific symptoms and raised CA125 or abnormal ultrasound results (or both) who had been referred via rapid access, elective clinics, or emergency presentations from 23 hospitals in the UK. Patients with normal CA125 and simple ovarian cysts of smaller than 5 cm in diameter, active non-ovarian malignancy, or previous ovarian malignancy, or those who were pregnant or declined a transvaginal scan, were ineligible. In this analysis, only postmenopausal participants were included. Participants completed a symptom questionnaire, gave a blood sample, and had transabdominal and transvaginal ultrasounds performed by International Ovarian Tumour Analysis consortium (IOTA)-certified sonographers. Index tests were Risk of Malignancy 1 (RMI1) at a threshold of 200, Risk of Malignancy Algorithm (ROMA) at multiple thresholds, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX) at thresholds of 3% and 10%, IOTA SRRisk model at thresholds of 3% and 10%, IOTA Simple Rules (malignant vs benign, or inconclusive), and CA125 at 35 IU/mL. In a post-hoc analysis, the Ovarian Adnexal and Reporting Data System (ORADS) at 10% was derived from IOTA ultrasound variables using established methods since ORADS was described after completion of recruitment. Index tests were conducted by study staff masked to the results of the reference standard. The comparator was RMI1 at the 250 threshold (the current UK National Health Service standard of care). The reference standard was surgical or biopsy tissue histology or cytology within 3 months, or a self-reported diagnosis of ovarian cancer at 12 month follow-up. The primary outcome was diagnostic accuracy at predicting primary invasive ovarian cancer versus benign or normal histology, assessed by analysing the sensitivity, specificity, C-index, area under receiver operating characteristic curve, positive and negative predictive values, and calibration plots in participants with conclusive reference standard results and available index test data. This study is registered with the International Standard Randomised Controlled Trial Number registry (ISRCTN17160843)., Findings: Between July 13, 2015, and Nov 30, 2018, 1242 postmenopausal patients were recruited, of whom 215 (17%) had primary ovarian cancer. 166 participants had missing, inconclusive, or other reference standard results; therefore, data from a maximum of 1076 participants were used to assess the index tests for the primary outcome. Compared with RMI1 at 250 (sensitivity 82·9% [95% CI 76·7 to 88·0], specificity 87·4% [84·9 to 89·6]), IOTA ADNEX at 10% was more sensitive (difference of -13·9% [-20·2 to -7·6], p<0·0001) but less specific (difference of 28·5% [24·7 to 32·3], p<0·0001). ROMA at 29·9 had similar sensitivity (difference of -3·6% [-9·1 to 1·9], p=0·24) but lower specificity (difference of 5·2% [2·5 to 8·0], p=0·0001). RMI1 at 200 had similar sensitivity (difference of -2·1% [-4·7 to 0·5], p=0·13) but lower specificity (difference of 3·0% [1·7 to 4·3], p<0·0001). IOTA SRRisk model at 10% had similar sensitivity (difference of -4·3% [-11·0 to -2·3], p=0·23) but lower specificity (difference of 16·2% [12·6 to 19·8], p<0·0001). IOTA Simple Rules had similar sensitivity (difference of -1·6% [-9·3 to 6·2], p=0·82) and specificity (difference of -2·2% [-5·1 to 0·6], p=0·14). CA125 at 35 IU/mL had similar sensitivity (difference of -2·1% [-6·6 to 2·3], p=0·42) but higher specificity (difference of 6·7% [4·3 to 9·1], p<0·0001). In a post-hoc analysis, when compared with RMI1 at 250, ORADS achieved similar sensitivity (difference of -2·1%, 95% CI -8·6 to 4·3, p=0·60) and lower specificity (difference of 10·2%, 95% CI 6·8 to 13·6, p<0·0001)., Interpretation: In view of its higher sensitivity than RMI1 at 250, despite some loss in specificity, we recommend that IOTA ADNEX at 10% should be considered as the new standard-of-care diagnostic in ovarian cancer for postmenopausal patients., Funding: UK National Institute of Heath Research., Competing Interests: Declaration of interests SS reports a research grant from AoA Diagnostics for work with samples collected in this study but not reported within this manuscript. SS reports honoraria from AstraZeneca, Merck, and GSK and consultancy from GSK and Immunogen, all unrelated to this work. TB reports grants, personal fees, and travel support from Samsung Medison; travel support from Roche Diagnostics; and personal fees from GE Healthcare, all outside the submitted work. BVC and DT report consultancy work done by KU Leuven to help the implementation and testing of the IOTA ADNEX model in ultrasound machines by Samsung Medison and GE Healthcare, outside the submitted work. UM declares stock ownership awarded by University College London until October, 2021, in Abcodia. UM and AG-M report research collaboration contracts with QIMR Berghofer Medical Research Institute, iLOF (intelligent Lab on Fiber), RNA Guardian, Micronoma, Mercy Bioanalytics, and Synteny Biotechnology. SK reports an honorary role as an Ovacome charity trustee. DT, TB, and BVC are IOTA steering group members and developed the IOTA models. All other authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objectives: To evaluate the ability of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and the International Ovarian Tumour Analysis (IOTA) two-step strategy to predict malignancy in adnexal masses detected in an outpatient low-risk setting, and to estimate the risk of complications in masses with benign ultrasound morphology managed using clinical and ultrasound follow-up., Methods: This single-center study was performed at Hospital Universitari Dexeus, Barcelona, Spain, using interim data from the ongoing prospective observational IOTA Phase-5 (IOTA5) study. The primary aim of the IOTA5 study is to describe the cumulative incidence of complications during follow-up of adnexal masses classified as benign on ultrasound examination. Consecutive patients with an adnexal mass detected between June 2012 and September 2016 in a private center offering screening for gynecological cancer were included and followed up until February 2020. Tumors were classified as benign or malignant based on histology (if patients underwent surgery) or the outcome of clinical and ultrasound follow-up at 12 (range, 10-14) months. Multiple imputation was used when outcomes were uncertain. The ability of the ADNEX model without CA125 and of the IOTA two-step strategy to distinguish benign from malignant masses was evaluated retrospectively using the prospectively collected data. We assessed performance with regard to discrimination (area under the receiver-operating-characteristics curve (AUC)), calibration, classification (sensitivity and specificity) and clinical utility (Net Benefit). In the group of patients with a mass judged to be benign who were selected for conservative management, we evaluated the occurrence of spontaneous resolution or any mass complication during the first 5 years of follow-up by assessing the cumulative incidence of malignancy, torsion, cyst rupture and minor mass complications (inflammation, infection or adhesions) and the time to occurrence of an event., Results: A total of 2654 patients were recruited to the study. After application of exclusion criteria, 2039 patients with a newly detected mass were included for the model validation. Of those, 1684 (83%) masses were benign, 49 (2%) masses were malignant and, for 306 (15%) masses, the outcome was uncertain and therefore imputed. The AUC was 0.95 (95% CI, 0.89-0.98) for ADNEX without CA125 and 0.94 (95% CI, 0.88-0.97) for the two-step strategy. Calibration performance could not be meaningfully interpreted because the small number of malignancies resulted in very wide confidence intervals. The two-step strategy had better clinical utility than did the ADNEX model at malignancy risk thresholds < 3%. There were 1472 (72%) patients whose mass was judged to be benign based on pattern recognition by an experienced ultrasound examiner and were managed with clinical and ultrasound follow-up. In this group, the 5-year cumulative incidence was 66% (95% CI, 63-69%) for spontaneous resolution of the mass, 0% (95% CI, 0-0.2%) for torsion, 0.1% (95% CI, < 0.1-0.4%) for cyst rupture, 0.2% (95% CI, 0.1-0.6%) for a borderline tumor and 0.2% (95% CI, 0.1-0.6%) for invasive malignancy., Conclusions: The ADNEX model and IOTA two-step strategy performed well to distinguish benign from malignant adnexal masses detected in a low-risk population. Conservative management is safe for masses with a benign ultrasound appearance in this population. © 2024 International Society of Ultrasound in Obstetrics and Gynecology., (© 2024 International Society of Ultrasound in Obstetrics and Gynecology.)

Objective: To investigate psychological correlates in women referred with suspected ovarian cancer via the fast-track pathway, explore how anxiety and distress levels change at 12 months post-testing, and report cancer conversion rates by age and referral pathway., Design: Single-arm prospective cohort study., Setting: Multicentre. Secondary care including outpatient clinics and emergency admissions., Population: A cohort of 2596 newly presenting symptomatic women with a raised CA125 level, abnormal imaging or both., Methods: Women completed anxiety and distress questionnaires at recruitment and at 12 months for those who had not undergone surgery or a biopsy within 3 months of recruitment., Main Outcome Measures: Anxiety and distress levels measured using a six-item short form of the State-Trait Anxiety Inventory (STAI-6) and the Impact of Event Scale - Revised (IES-r) questionnaire. Ovarian cancer (OC) conversion rates by age, menopausal status and referral pathway., Results: Overall, 1355/2596 (52.1%) and 1781/2596 (68.6%) experienced moderate-to-severe distress and anxiety, respectively, at recruitment. Younger age and emergency presentations had higher distress levels. The clinical category for anxiety and distress remained unchanged/worsened in 76% of respondents at 12 months, despite a non-cancer diagnosis. The OC rates by age were 1.6% (95% CI 0.5%-5.9%) for age <40 years and 10.9% (95% CI 8.7%-13.6%) for age ≥40 years. In women referred through fast-track pathways, 3.3% (95% CI 1.9%-5.7%) of pre- and 18.5% (95% CI 16.1%-21.0%) of postmenopausal women were diagnosed with OC., Conclusions: Women undergoing diagnostic testing display severe anxiety and distress. Younger women are especially vulnerable and should be targeted for support. Women under the age of 40 years have low conversion rates and we advocate reducing testing in this group to reduce the harms of testing., (© 2024 The Authors. BJOG: An International Journal of Obstetrics and Gynaecology published by John Wiley & Sons Ltd.)

Background: Several diagnostic prediction models to help clinicians discriminate between benign and malignant adnexal masses are available. This study is a head-to-head comparison of the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with that of the Risk of Ovarian Malignancy Algorithm (ROMA)., Methods: This is a retrospective study based on prospectively included consecutive women with an adnexal tumour scheduled for surgery at five oncology centres and one non-oncology centre in four countries between 2015 and 2019. The reference standard was histology. Model performance for ADNEX and ROMA was evaluated regarding discrimination, calibration, and clinical utility., Results: The primary analysis included 894 patients, of whom 434 (49%) had a malignant tumour. The area under the receiver operating characteristic curve (AUC) was 0.92 (95% CI 0.88-0.95) for ADNEX with CA125, 0.90 (0.84-0.94) for ADNEX without CA125, and 0.85 (0.80-0.89) for ROMA. ROMA, and to a lesser extent ADNEX, underestimated the risk of malignancy. Clinical utility was highest for ADNEX. ROMA had no clinical utility at decision thresholds <27%., Conclusions: ADNEX had better ability to discriminate between benign and malignant adnexal tumours and higher clinical utility than ROMA., Clinical Trial Registration: clinicaltrials.gov NCT01698632 and NCT02847832., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses., Methods: This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235., Results: The cohort had a median age of 53 years old (range 20-81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral., Conclusions: Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes., (© 2024. The Author(s).)

Background: Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage I primary invasive, stage II-IV primary invasive, or secondary metastatic., Methods: This retrospective cohort study used 5909 patients recruited from 1999 to 2012 for model development, and 3199 patients recruited from 2012 to 2015 for model validation. Patients were recruited at oncology referral or general centers and underwent an ultrasound examination and surgery ≤ 120 days later. We developed models using standard multinomial logistic regression (MLR), Ridge MLR, random forest (RF), XGBoost, neural networks (NN), and support vector machines (SVM). We used nine clinical and ultrasound predictors but developed models with or without CA125., Results: Most tumors were benign (3980 in development and 1688 in validation data), secondary metastatic tumors were least common (246 and 172). The c-statistic (AUROC) to discriminate benign from any type of malignant tumor ranged from 0.89 to 0.92 for models with CA125, from 0.89 to 0.91 for models without. The multiclass c-statistic ranged from 0.41 (SVM) to 0.55 (XGBoost) for models with CA125, and from 0.42 (SVM) to 0.51 (standard MLR) for models without. Multiclass calibration was best for RF and XGBoost. Estimated probabilities for a benign tumor in the same patient often differed by more than 0.2 (20% points) depending on the model. Net Benefit for diagnosing malignancy was similar for algorithms at the commonly used 10% risk threshold, but was slightly higher for RF at higher thresholds. Comparing models, between 3% (XGBoost vs. NN, with CA125) and 30% (NN vs. SVM, without CA125) of patients fell on opposite sides of the 10% threshold., Conclusion: Although several models had similarly good performance, individual probability estimates varied substantially., (© 2023. The Author(s).)

Importance: Correct diagnosis of ovarian cancer results in better prognosis. Adnexal lesions can be stratified into the Ovarian-Adnexal Reporting and Data System (O-RADS) risk of malignancy categories with either the O-RADS lexicon, proposed by the American College of Radiology, or the International Ovarian Tumor Analysis (IOTA) 2-step strategy., Objective: To investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy., Design, Setting, and Participants: Retrospective external diagnostic validation study based on interim data of IOTA5, a prospective international multicenter cohort study, in 36 oncology referral centers or other types of centers. A total of 8519 consecutive adult patients presenting with an adnexal mass between January 1, 2012, and March 1, 2015, and treated either with surgery or conservatively were included in this diagnostic study. Twenty-five patients were excluded for withdrawal of consent, 2777 were excluded from 19 centers that did not meet predefined data quality criteria, and 812 were excluded because they were already in follow-up at recruitment. The analysis included 4905 patients with a newly detected adnexal mass in 17 centers that met predefined data quality criteria. Data were analyzed from January 31 to March 1, 2022., Exposures: Stratification into O-RADS categories (malignancy risk <1%, 1% to <10%, 10% to <50%, and ≥50%). For the IOTA 2-step strategy, the stratification is based on the individual risk of malignancy calculated with the IOTA 2-step strategy., Main Outcomes and Measures: Observed prevalence of malignancy in each O-RADS risk category, as well as sensitivity and specificity. The reference standard was the status of the tumor at inclusion, determined by histology or clinical and ultrasonographic follow-up for 1 year. Multiple imputation was used for uncertain outcomes owing to inconclusive follow-up information., Results: Median age of the 4905 patients was 48 years (IQR, 36-62 years). Data on race and ethnicity were not collected. A total of 3441 tumors (70%) were benign, 978 (20%) were malignant, and 486 (10%) had uncertain classification. Using the O-RADS lexicon resulted in 1.1% (24 of 2196) observed prevalence of malignancy in O-RADS 2, 4% (34 of 857) in O-RADS 3, 27% (246 of 904) in O-RADS 4, and 78% (732 of 939) in O-RADS 5; the corresponding results for the IOTA 2-step strategy were 0.9% (18 of 1984), 4% (58 of 1304), 30% (206 of 690), and 82% (756 of 927). At the 10% risk threshold (O-RADS 4-5), the O-RADS lexicon had 92% sensitivity (95% CI, 87%-96%) and 80% specificity (95% CI, 74%-85%), and the IOTA 2-step strategy had 91% sensitivity (95% CI, 84%-95%) and 85% specificity (95% CI, 80%-88%)., Conclusions and Relevance: The findings of this external diagnostic validation study suggest that both the O-RADS lexicon and the IOTA 2-step strategy can be used to stratify patients into risk groups. However, the observed malignancy rate in O-RADS 2 was not clearly below 1%.

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.)

Background: Tumors can influence peripheral immune macroenvironment, thereby creating opportunities for non-invasive serum/plasma immunobiomarkers for immunostratification and immunotherapy designing. However, current approaches for immunobiomarkers' detection are largely quantitative, which is unreliable for assessing functional peripheral immunodynamics of patients with cancer. Hence, we aimed to design a functional biomarker modality for capturing peripheral immune signaling in patients with cancer for reliable immunostratification., Methods: We used a data-driven in silico framework, integrating existing tumor/blood bulk-RNAseq or single-cell (sc)RNAseq datasets of patients with cancer, to inform the design of an innovative serum-screening modality, that is, serum-functional immunodynamic status (sFIS) assay. Next, we pursued proof-of-concept analyses via multiparametric serum profiling of patients with ovarian cancer (OV) with sFIS assay combined with Luminex (cytokines/soluble immune checkpoints), CA125-antigen detection, and whole-blood immune cell counts. Here, sFIS assay's ability to determine survival benefit or malignancy risk was validated in a discovery (n=32) and/or validation (n=699) patient cohorts. Lastly, we used an orthotopic murine metastatic OV model, with anti-OV therapy selection via in silico drug-target screening and murine serum screening via sFIS assay, to assess suitable in vivo immunotherapy options., Results: In silico data-driven framework predicted that peripheral immunodynamics of patients with cancer might be best captured via analyzing myeloid nuclear factor kappa-light-chain enhancer of activated B cells (NFκB) signaling and interferon-stimulated genes' (ISG) responses. This helped in conceptualization of an ' in sitro ' ( in vitro + in situ ) sFIS assay, where human myeloid cells were exposed to patients' serum in vitro , to assess serum-induced (si)-NFκB or interferon (IFN)/ISG responses (as active signaling reporter activity) within them, thereby 'mimicking' patients' in situ immunodynamic status. Multiparametric serum profiling of patients with OV established that sFIS assay can: decode peripheral immunology (by indicating higher enrichment of si-NFκB over si-IFN/ISG responses), estimate survival trends (si-NFκB or si-IFN/ISG responses associating with negative or positive prognosis, respectively), and coestimate malignancy risk (relative to benign/borderline ovarian lesions). Biologically, we documented dominance of pro-tumorigenic, myeloid si-NFκB response HIGH si-IFN/ISG response LOW inflammation in periphery of patients with OV. Finally, in an orthotopic murine metastatic OV model, sFIS assay predicted the higher capacity of chemo-immunotherapy (paclitaxel-carboplatin plus anti-TNF antibody combination) in achieving a pro-immunogenic peripheral milieu (si-IFN/ISG response HIGH si-NFκB response LOW ), which aligned with high antitumor efficacy., Conclusions: We established sFIS assay as a novel biomarker resource for serum screening in patients with OV to evaluate peripheral immunodynamics, patient survival trends and malignancy risk, and to design preclinical chemo-immunotherapy strategies., Competing Interests: Competing interests: The sFIS assay is currently the subject of an ongoing PCT patent application. ADG has received consulting/advisory/lecture honoraria from Boehringer Ingelheim and Miltenyi Biotec., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The current review sums up the literature on the diagnostic performance of models to predict malignancy in adnexal masses and the ability of ultrasound to make a specific diagnosis in adnexal masses. A summary of the role of ultrasound in assessing the extension of malignant ovarian disease is also provided.

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group, and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the pre-operative diagnosis of ovarian tumors, including imaging techniques, biomarkers, and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the pre-operative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the pre-operative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement., Competing Interests: Competing interests: DT: senior investigator FWO (Fund for Scientific Research Flanders), and research sponsored by Roche Diagnostics. KU Leuven has consultancy agreements with GE Healthcare, Samsung Healthcare, GSK, and Canon. TB: research sponsored by Roche Diagnostics, Samsung Medison and Illumina, and grants for traveling from Samsung Medison. LC: advisory boards for AstraZeneca, GSK, Takeda, and Roche. DC: advisory boards for Genmab, AstraZeneca, Roche, and Sotio. NC: advisory boards for AstraZeneca, Seattle Genetics, Mersana and eTheRNA Immunotherapies NV, grants for traveling from Roche, Genmab and Amgen, and educational fees from MSD and Medscape Oncology. AdB: advisory boards for Roche, AstraZeneca, GSK/Tesaro, BIOCAD, Clovis, Genmab/Seattle Genetics, Pfizer, and Amgen, and grants for traveling from Roche and AstraZeneca. IV: consulting activities for Amgen, AstraZeneca, Clovis Oncology, Carrick Therapeutics, Debiopharm International SA, Deciphera Pharmaceuticals, Elevar Therapeutics, F Hoffmann-La Roche Ltd, Genmab, GSK, Immunogen Inc, Medical University of Vienna, Mersana, Millenium Pharmaceuticals, MSD, Novocure, Octimet Oncology NV, Oncoinvent AS, Pharmamar, Sotioa.s, Tesaro Inc, Verastem Oncology, and Zentalis, contracted research (via KU Leuven) from Oncoinvent AS and Genmab, grants (corporate sponsored research) from Amgen and Roche, and accommodations/travel expenses from Amgen, MSD, Tesaro, AstraZeneca, and Roche. CF: advisory boards for Roche, GSK, Tesaro, AZ/MSD, Clovis, Sequana and Ethicon, and grants for traveling from GSK and Roche. FP, CL, DF, WF, GG, BL, AL, LM, PM, DQ, ACT, VV and GS: no conflicts of interest., (© IGCS and ESGO 2021. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ.)

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumors, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

Background: Peri-operative variables associated with prolonged Intensive Care Unit (ICU) admission following cytoreductive surgery for ovarian cancer were investigated., Patients and Methods: A retrospective review was carried out of patients admitted to the ICU following cytoreductive surgery for ovarian cancer in a single tertiary referral centre from 2015-2019. Patients were categorized according to length of ICU stay (<48 h and ≥48 h), and peri-operative variables were compared across the two groups., Results: A total of 56 patients were admitted to the ICU post-operatively, 37 for <48 h and 19 for ≥48 h (range=3-11 days). Greater duration of procedure and estimated blood loss, bowel resection, higher post-operative lactate level, lower post-operative albumin level and requirement for post-operative blood products were associated with prolonged ICU stay. Increased intraoperative fluid requirement was an independent predictor of extended ICU stay., Conclusion: Utilizing identified intra-operative risk factors to perform individualized risk assessments might improve planning of ICU resources. Optimizing intraoperative fluid management may improve short-term patient outcomes., (Copyright © 2021 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis changes the texture of cellular networks of a mass/tumor has been informing such diagnostics systems with use of more suitable image texture features and their extraction methods. Several texture features have been recently applied in discriminating malignant and benign ovarian masses by analysing B-mode images from ultrasound scan of the ovary with different levels of performance. However, comparative performance evaluation of these reported features using common sets of clinically approved images is lacking. This paper presents an empirical evaluation of seven commonly used texture features (histograms, moments of histogram, local binary patterns [256-bin and 59-bin], histograms of oriented gradients, fractal dimensions, and Gabor filter), using a collection of 242 ultrasound scan images of ovarian masses of various pathological characteristics. The evaluation examines not only the effectiveness of classification schemes based on the individual texture features but also the effectiveness of various combinations of these schemes using the simple majority-rule decision level fusion. Trained support vector machine classifiers on the individual texture features without any specific pre-processing, achieve levels of accuracy between 75% and 85% where the seven moments and the 256-bin LBP are at the lower end while the Gabor filter is at the upper end. Combining the classification results of the top k ( k  = 3, 5, 7) best performing features further improve the overall accuracy to a level between 86% and 90%. These evaluation results demonstrate that each of the investigated image-based texture features provides informative support in distinguishing benign or malignant ovarian masses.

Competing Interests: Competing interests: None declared.

Objective: To estimate the diagnostic value of tumor and immune related proteins in the discrimination between benign and malignant adnexal masses, and between different subgroups of tumors., Methods: In this exploratory diagnostic study, 254 patients with an adnexal mass scheduled for surgery were consecutively enrolled at the University Hospitals Leuven (128 benign, 42 borderline, 22 stage I, 55 stage II-IV, and 7 secondary metastatic tumors). The quantification of 33 serum proteins was done preoperatively, using multiplex high throughput immunoassays (Luminex) and electrochemiluminescence immuno-assay (ECLIA). We calculated univariable areas under the Receiver Operating Characteristic Curves (AUCs). To discriminate malignant from benign tumors, multivariable ridge logistic regression with backward elimination was performed, using bootstrapping to validate the resulting AUCs., Results: CA125 had the highest univariable AUC to discriminate malignant from benign tumors (0.85, 95% confidence interval 0.79-0.89). Combining CA125 with CA72.4 and HE4 increased the AUC to 0.87. For benign vs borderline tumors, CA125 had the highest univariable AUC (0.74). For borderline vs stage I malignancy, no proteins were promising. For stage I vs II-IV malignancy, CA125, HE4, CA72.4, CA15.3 and LAP had univariable AUCs ≥0.80., Conclusions: The results confirm the dominant role of CA125 for identifying malignancy, and suggest that other markers (HE4, CA72.4, CA15.3 and LAP) may help to distinguish between stage I and stage II-IV malignancies. However, further research is needed, also to investigate the added value over clinical and ultrasound predictors of malignancy, focusing on the differentiation between subtypes of malignancy., Competing Interests: Declaration of Competing Interest TB reports conflicts of interests with Roche Diagnostics, outside the submitted work. All other authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The Ovarian-Adnexal Reporting and Data System (O-RADS) US risk stratification and management system is designed to provide consistent interpretations, to decrease or eliminate ambiguity in US reports resulting in a higher probability of accuracy in assigning risk of malignancy to ovarian and other adnexal masses, and to provide a management recommendation for each risk category. It was developed by an international multidisciplinary committee sponsored by the American College of Radiology and applies the standardized reporting tool for US based on the 2018 published lexicon of the O-RADS US working group. For risk stratification, the O-RADS US system recommends six categories (O-RADS 0-5), incorporating the range of normal to high risk of malignancy. This unique system represents a collaboration between the pattern-based approach commonly used in North America and the widely used, European-based, algorithmic-style International Ovarian Tumor Analysis (IOTA) Assessment of Different Neoplasias in the Adnexa model system, a risk prediction model that has undergone successful prospective and external validation. The pattern approach relies on a subgroup of the most predictive descriptors in the lexicon based on a retrospective review of evidence prospectively obtained in the IOTA phase 1-3 prospective studies and other supporting studies that assist in differentiating management schemes in a variety of almost certainly benign lesions. With O-RADS US working group consensus, guidelines for management in the different risk categories are proposed. Both systems have been stratified to reach the same risk categories and management strategies regardless of which is initially used. At this time, O-RADS US is the only lexicon and classification system that encompasses all risk categories with their associated management schemes., (© RSNA, 2019.)

Introduction: Ovarian tumors are the most common diagnostic challenge for gynecologists and ultrasound examination has become the main technique for assessment of ovarian pathology and for preoperative distinction between malignant and benign ovarian tumors. However, ultrasonography is highly examiner-dependent and there may be an important variability between two different specialists when examining the same case. The objective of this work is the evaluation of different well-known Machine Learning (ML) systems to perform the automatic categorization of ovarian tumors from ultrasound images., Methods: We have used a real patient database whose input features have been extracted from 348 images, from the IOTA tumor images database, holding together with the class labels of the images. For each patient case and ultrasound image, its input features have been previously extracted using Fourier descriptors computed on the Region Of Interest (ROI). Then, four ML techniques are considered for performing the classification stage: K-Nearest Neighbors (KNN), Linear Discriminant (LD), Support Vector Machine (SVM) and Extreme Learning Machine (ELM)., Results: According to our obtained results, the KNN classifier provides inaccurate predictions (less than 60% of accuracy) independently of the size of the local approximation, whereas the classifiers based on LD, SVM and ELM are robust in this biomedical classification (more than 85% of accuracy)., Conclusions: ML methods can be efficiently used for developing the classification stage in computer-aided diagnosis systems of ovarian tumor from ultrasound images. These approaches are able to provide automatic classification with a high rate of accuracy. Future work should aim at enhancing the classifier design using ensemble techniques. Another ongoing work is to exploit different kind of features extracted from ultrasound images., Competing Interests: The authors have declared that no competing interests exist.

Background: Ovarian tumours are usually surgically removed because of the presumed risk of complications. Few large prospective studies on long-term follow-up of adnexal masses exist. We aimed to estimate the cumulative incidence of cyst complications and malignancy during the first 2 years of follow-up after adnexal masses have been classified as benign by use of ultrasonography., Methods: In the international, prospective, cohort International Ovarian Tumor Analysis Phase 5 (IOTA5) study, patients aged 18 years or older with at least one adnexal mass who had been selected for surgery or conservative management after ultrasound assessment were recruited consecutively from 36 cancer and non-cancer centres in 14 countries. Follow-up of patients managed conservatively is ongoing at present. In this 2-year interim analysis, we analysed patients who were selected for conservative management of an adnexal mass judged to be benign on ultrasound on the basis of subjective assessment of ultrasound images. Conservative management included ultrasound and clinical follow-up at intervals of 3 months and 6 months, and then every 12 months thereafter. The main outcomes of this 2-year interim analysis were cumulative incidence of spontaneous resolution of the mass, torsion or cyst rupture, or borderline or invasive malignancy confirmed surgically in patients with a newly diagnosed adnexal mass. IOTA5 is registered with ClinicalTrials.gov, number NCT01698632, and the central Ethics Committee and the Belgian Federal Agency for Medicines and Health Products, number S51375/B32220095331, and is ongoing., Findings: Between Jan 1, 2012, and March 1, 2015, 8519 patients were recruited to IOTA5. 3144 (37%) patients selected for conservative management were eligible for inclusion in our analysis, of whom 221 (7%) had no follow-up data and 336 (11%) were operated on before a planned follow-up scan was done. Of 2587 (82%) patients with follow-up data, 668 (26%) had a mass that was already in follow-up at recruitment, and 1919 (74%) presented with a new mass at recruitment (ie, not already in follow-up in the centre before recruitment). Median follow-up of patients with new masses was 27 months (IQR 14-38). The cumulative incidence of spontaneous resolution within 2 years of follow-up among those with a new mass at recruitment (n=1919) was 20·2% (95% CI 18·4-22·1), and of finding invasive malignancy at surgery was 0·4% (95% CI 0·1-0·6), 0·3% (<0·1-0·5) for a borderline tumour, 0·4% (0·1-0·7) for torsion, and 0·2% (<0·1-0·4) for cyst rupture., Interpretation: Our results suggest that the risk of malignancy and acute complications is low if adnexal masses with benign ultrasound morphology are managed conservatively, which could be of value when counselling patients, and supports conservative management of adnexal masses classified as benign by use of ultrasound., Funding: Research Foundation Flanders, KU Leuven, Swedish Research Council., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objectives: To identify ultrasound features of papillations or of the cyst wall that can discriminate between benign and malignant unilocular-solid cysts with papillations but no other solid components., Methods: From the International Ovarian Tumor Analysis (IOTA) database derived from seven ultrasound centers, we identified patients with an adnexal lesion described at ultrasonography as unilocular-solid with papillations but no other solid components. All patients had undergone transvaginal ultrasound between 1999 and 2007 or 2009 and 2012, by an experienced examiner following the IOTA research protocol. Information on four ultrasound features of papillations had been collected prospectively. Information on a further seven ultrasound features was collected retrospectively from electronic or paper ultrasound images of good quality. The histological diagnosis of the surgically removed adnexal lesion was considered the gold standard., Results: Of 204 masses included, 131 (64.2%) were benign, 42 (20.6%) were borderline tumors, 30 (14.7%) were primary invasive tumors and one (0.5%) was a metastasis. Multivariate logistic regression analysis showed the following ultrasound features to be associated independently with malignancy: height of the largest papillation, presence of blood flow in papillations, papillation confluence or dissemination, and shadows behind papillations. Shadows decreased the odds of malignancy, while the other features increased them., Conclusion: We have identified ultrasound features that can help to discriminate between benign and malignant unilocular-solid cysts with papillations but no other solid components. Our results need to be confirmed in prospective studies. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd., (Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.)

Purpose: To evaluate the utility of preoperative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and 3 models from the International Ovarian Tumor Analysis (IOTA) group [LR2, ADNEX, and the Simple Rules risk score (SRRisk)]. Experimental Design: A secondary analysis of prospectively collected data from 2 cross-sectional cohort studies was performed to externally validate diagnostic models. A total of 2,763 patients (2,403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 nononcology hospitals) in 6 countries participated. Excised tissue was histologically classified as benign or malignant. The clinical utility of the preoperative diagnostic models was assessed with net benefit (NB) at a range of risk thresholds (5%-50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals. Results: The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10% to 15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks, and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology vs. nononcology) were similar. Conclusions: All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care. Clin Cancer Res; 23(17); 5082-90. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Background: The International Ovarian Tumour Analysis (IOTA) group have developed the ADNEX (The Assessment of Different NEoplasias in the adneXa) model to predict the risk that an ovarian mass is benign, borderline, stage I, stages II-IV or metastatic. We aimed to externally validate the ADNEX model in the hands of examiners with varied training and experience., Methods: This was a multicentre cross-sectional cohort study for diagnostic accuracy. Patients were recruited from three cancer centres in Europe. Patients who underwent transvaginal ultrasonography and had a histological diagnosis of surgically removed tissue were included. The diagnostic performance of the ADNEX model with and without the use of CA125 as a predictor was calculated., Results: Data from 610 women were analysed. The overall prevalence of malignancy was 30%. The area under the receiver operator curve (AUC) for the ADNEX diagnostic performance to differentiate between benign and malignant masses was 0.937 (95% CI: 0.915-0.954) when CA125 was included, and 0.925 (95% CI: 0.902-0.943) when CA125 was excluded. The calibration plots suggest good correspondence between the total predicted risk of malignancy and the observed proportion of malignancies. The model showed good discrimination between the different subtypes., Conclusions: The performance of the ADNEX model retains its performance on external validation in the hands of ultrasound examiners with varied training and experience., Competing Interests: TB reports that clinical research in his department (QCCH, Imperial College London Healthcare NHS Trust) is supported by Samsung Medison and Roche Diagnostics. The remaining authors declare no conflict of interest.

Introduction: Ovarian cancer (OC) is associated with non-specific symptoms such as bloating, making accurate diagnosis challenging: only 1 in 3 women with OC presents through primary care referral. National Institute for Health and Care Excellence guidelines recommends sequential testing with CA125 and routine ultrasound in primary care. However, these diagnostic tests have limited sensitivity or specificity. Improving accurate triage in women with vague symptoms is likely to improve mortality by streamlining referral and care pathways. The Refining Ovarian Cancer Test Accuracy Scores (ROCkeTS; HTA 13/13/01) project will derive and validate new tests/risk prediction models that estimate the probability of having OC in women with symptoms. This protocol refers to the prospective study only (phase III)., Methods and Analysis: ROCkeTS comprises four parallel phases. The full ROCkeTS protocol can be found at http://www.birmingham.ac.uk/ROCKETS. Phase III is a prospective test accuracy study. The study will recruit 2450 patients from 15 UK sites. Recruited patients complete symptom and anxiety questionnaires, donate a serum sample and undergo ultrasound scored as per International Ovarian Tumour Analysis (IOTA) criteria. Recruitment is at rapid access clinics, emergency departments and elective clinics. Models to be evaluated include those based on ultrasound derived by the IOTA group and novel models derived from analysis of existing data sets. Estimates of sensitivity, specificity, c-statistic (area under receiver operating curve), positive predictive value and negative predictive value of diagnostic tests are evaluated and a calibration plot for models will be presented. ROCkeTS has received ethical approval from the NHS West Midlands REC (14/WM/1241) and is registered on the controlled trials website (ISRCTN17160843) and the National Institute of Health Research Cancer and Reproductive Health portfolios., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Objectives: To assess the diagnostic performance of subjective assessment by Level II ultrasound examiners in predicting the specific histology of adnexal masses., Methods: The women included in this prospective multicenter cross-sectional study were older than 16 years of age and had at least one adnexal mass. They underwent transvaginal sonography (TVS) performed by Level II examiners, all of whom were familiar with the International Ovarian Tumor Analysis (IOTA) group definitions of ultrasound features of ovarian masses. The final outcome was histology. Specific diagnoses were categorized into 16 groups. Agreement between subjective assessment and final histology was measured using unweighted kappa coefficients. Sensitivities and specificities were obtained for subjective assessment., Results: Of the 1279 women who underwent TVS, 313 were included in the final analysis. Overall agreement (16 × 16 table) between subjective assessment and histology was moderate, with a Cohen's kappa coefficient of 0.59 (95% CI, 0.53-0.65). The specificity of subjective assessment ranged between 91% and 100% for all histological subgroups. Highest sensitivities were achieved in the diagnosis of simple cysts (100% (95% CI, 61-100%)), hydrosalpinges (100% (95% CI, 34-100%)), mature teratomas (88% (95% CI, 74-96%)), endometriomas (75% (95% CI, 61-85%)), ovarian fibromas (88% (95% CI, 47-100%)), tubo-ovarian abscesses (88% (95% CI, 47-100%)) and serous cystadenocarcinomas (82% (95% CI, 66-93%)). Serous cystadenomas were misdiagnosed most commonly (40.5%). The sensitivity of subjective assessment in diagnosing adnexal torsion was 54% (95% CI, 25-81%); the 17 confirmed and/or suspected cases of adnexal torsion were not included in the 313 cases examined and analyzed for diagnostic performance., Conclusion: Overall, subjective assessment by Level II examiners was good for the detection of simple cysts, endometriomas, mature teratomas, hydrosalpinges, fibroma, tubo-ovarian abscess and serous cystadenocarcinomas., (Copyright © 2014 ISUOG. Published by John Wiley & Sons Ltd.)

Characterizing ovarian masses enables patients with malignancy to be appropriately triaged for treatment by subspecialist gynecological oncologists, which has been shown to optimize care and improve survival. Furthermore, correctly classifying benign masses facilitates the selection of patients with ovarian pathology that may either not require intervention, or be suitable for minimal access surgery if intervention is required. However, predicting whether a mass is benign or malignant is not the only clinically relevant information that we need to know before deciding on appropriate treatment. Knowing the specific histology of a mass is becoming of increasing importance as management options become more tailored to the individual patient. For example predicting a mucinous borderline tumor gives the opportunity for fertility sparing surgery, and will highlight the need for further gastrointestinal assessment. For benign disease, predicting the presence of an endometrioma and possible deeply infiltrating endometriosis is important when considering both who should perform and the extent of surgery. An examiner's subjective assessment of the morphological and vascular features of a mass using ultrasonography has been shown to be highly effective for predicting whether a mass is benign or malignant. Many masses also have features that enable a reliable diagnosis of the specific pathology of a particular mass to be made. In this narrative review we aim to describe the typical morphological features seen on ultrasound of different adnexal masses and illustrate these by showing representative ultrasound images.

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: The aim of this study is to assess whether the pretreatment serum HE4 levels or the Risk of Ovarian Malignancy Algorithm (ROMA) scores at the time of initial diagnosis are associated with progression-free survival (PFS) and disease-specific survival (DSS) in patients with ovarian cancer receiving either primary debulking surgery or neoadjuvant chemotherapy followed by interval debulking surgery., Methods: A survival analysis of 101 cases of invasive ovarian cancer recruited in a previous diagnostic accuracy study was conducted from 2005 to 2009 at the University Hospital KU Leuven, Belgium. Serum HE4 levels (pM) and ROMA scores (%) were obtained before primary treatment. Dates of death were obtained by record linkage with patient hospital files. Progression was evaluated according to the Response Evaluation Criteria in Solid Tumors. Adjusted hazards ratios (HRs) were estimated using multivariable Cox regression., Results: Eighty patients (79%) with invasive ovarian cancer underwent primary debulking surgery, whereas 21 (21%) received neoadjuvant chemotherapy. The median DSS was 3.72 years (95% confidence interval [CI], 3.19-4.07). Fifty-two patients (51%) died of disease, and 74 patients (73%) had progressive disease during follow-up. On univariable analysis, elevated pretreatment HE4 levels and ROMA scores were related to worse prognosis. However, after the adjustment for classic prognostic variables, HE4 levels (log2-transformed) and ROMA scores were unrelated to DSS (log-2 HE4: adjusted HR, 1.01; 95% CI, 0.84-1.21 and ROMA: adjusted HR per 10% increase, 0.96; 95% CI, 0.84-1.12) and PFS (log-2 HE4: adjusted HR, 0.98; 95% CI, 0.84-1.13 and ROMA: adjusted HR per 10% increase, 0.98; 95% CI, 0.88-1.11)., Conclusions: Pretreatment HE4 levels and ROMA scores are not independent prognostic factors for DSS and PFS after multivariable adjustment in patients with ovarian cancer.

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.

BACKGROUND Characterizing ovarian pathology is fundamental to optimizing management in both pre- and post-menopausal women. Inappropriate referral to oncology services can lead to unnecessary surgery or overly radical interventions compromising fertility in young women, whilst the consequences of failing to recognize cancer significantly impact on prognosis. By reflecting on recent developments of new diagnostic tests for preoperative identification of malignant disease in women with adnexal masses, we aimed to update a previous systematic review and meta-analysis. METHODS An extended search was performed in MEDLINE (PubMed) and EMBASE (OvidSp) from March 2008 to October 2013. Eligible studies provided information on diagnostic test performance of models, designed to predict ovarian cancer in a preoperative setting, that contained at least two variables. Study selection and extraction of study characteristics, types of bias, and test performance was performed independently by two reviewers. Quality was assessed using a modified version of the QUADAS assessment tool. A bivariate hierarchical random effects model was used to produce summary estimates of sensitivity and specificity with 95% confidence intervals or plot summary ROC curves for all models considered. RESULTS Our extended search identified a total of 1542 new primary articles. In total, 195 studies were eligible for qualitative data synthesis, and 96 validation studies reporting on 19 different prediction models met the predefined criteria for quantitative data synthesis. These models were tested on 26 438 adnexal masses, including 7199 (27%) malignant and 19 239 (73%) benign masses. The Risk of Malignancy Index (RMI) was the most frequently validated model. The logistic regression model LR2 with a risk cut-off of 10% and Simple Rules (SR), both developed by the International Ovarian Tumor Analysis (IOTA) study, performed better than all other included models with a pooled sensitivity and specificity, respectively, of 0.92 [95% CI 0.88-0.95] and 0.83 [95% CI 0.77-0.88] for LR2 and 0.93 [95% CI 0.89-0.95] and 0.81 [95% CI 0.76-0.85] for SR. A meta-analysis of centre-specific results stratified for menopausal status of two multicentre cohorts comparing LR2, SR and RMI-1 (using a cut-off of 200) showed a pooled sensitivity and specificity in premenopausal women for LR2 of 0.85 [95% CI 0.75-0.91] and 0.91 [95% CI 0.83-0.96] compared with 0.93 [95% CI 0.84-0.97] and 0.83 [95% CI 0.73-0.90] for SR and 0.44 [95% CI 0.28-0.62] and 0.95 [95% CI 0.90-0.97] for RMI-1. In post-menopausal women, sensitivity and specificity of LR2, SR and RMI-1 were 0.94 [95% CI 0.89-0.97] and 0.70 [95% CI 0.62-0.77], 0.93 [95% CI 0.88-0.96] and 0.76 [95% CI 0.69-0.82], and 0.79 [95% CI 0.72-0.85] and 0.90 [95% CI 0.84-0.94], respectively. CONCLUSIONS An evidence-based approach to the preoperative characterization of any adnexal mass should incorporate the use of IOTA Simple Rules or the LR2 model, particularly for women of reproductive age.

Objective: To determine whether serum human-epididymis protein-4 (HE4) levels or Risk of Ovarian Malignancy Algorithm (ROMA) scores are useful second-stage tests for tumors thought to be difficult to characterize as benign or malignant on the basis of ultrasound findings by experienced examiners, and to investigate whether adding information on serum HE4 levels or ROMA scores to ultrasound findings improves diagnostic performance., Methods: This was a prospective cross-sectional diagnostic accuracy study conducted in a tertiary referral center that enrolled consecutive women with a known adnexal mass scheduled for surgery. Experienced level III examiners classified each mass as certainly or probably benign, difficult to classify, or probably or certainly malignant after preoperative ultrasound examination. Serum HE4 and CA 125 levels were measured before surgery., Results: The final database comprised 360 women, of whom 216 (60%) had benign and 144 (40%) had malignant disease. Examiners were highly confident in 196 cases (54%), moderately confident in 135 (38%) and completely uncertain about their diagnosis in 29 (8%) cases. With a sensitivity of 67% and specificity of 70%, subjective assessment outperformed HE4 and ROMA in the subgroup of difficult tumors. Both tests had low discriminatory capacity with poor areas under the receiver-operating characteristics curve of 0.536 (95% CI, 0.302-0.771) and 0.565 (95% CI, 0.294-0.836), respectively. A strategy that incorporates sequential testing of serum HE4 or ROMA scores after transvaginal ultrasonography resulted in a deterioration in overall test performance., Conclusion: Measurement of serum HE4 or calculating scores using the ROMA as secondary tests does not seem useful for classifying adnexal tumors after subjective assessment with transvaginal ultrasonography., (Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.)

Objectives: To evaluate the diagnostic performance of the IOTA (International Ovarian Tumor Analysis group) (clinically oriented three-step strategy for preoperative characterization of ovarian masses when ultrasonography is performed by examiners with different background training and experience., Methods: A 27-month prospective multicenter cross-sectional study was performed. 36 level II ultrasound examiners contributed in three UK hospitals. Transvaginal ultrasonography was performed using a standardized approach. Step one uses simple descriptors (SD), step two ultrasound simple rules (SR) and step three subjective assessment of ultrasound images (SA) by examiners. The final outcome was findings at surgery and the histological diagnosis of surgically removed masses., Results: 1165 women with adnexal masses underwent transvaginal ultrasonography, 301 had surgery. Prevalence of malignancy was 31% (n=92). SD were able to classify 46% of the masses into benign or malignant (step one), with a sensitivity of 93% and specificity of 97%. Applying SD followed by SR to residual unclassified masses by SD enabled 89% of all masses (n=268) to be classified with a sensitivity 95% of and specificity of 95%. SA was then used to evaluate the rest of the masses. Compared to the risk of malignancy index (RMI), the sensitivity and specificity for the three-step (SD+SR+SA) strategy were 93% (95% CI: 86-97%) and 92% (95% CI: 87-95%) vs. 72% (95% CI: 62-80%) and 95% (95% CI: 91-97%) for RMI, respectively., Conclusion: The IOTA three-step strategy shows good test performance on external validation in the hands of ultrasonography examiners with different background training and experience. This performance is considerably better than the RMI., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: Correct characterisation of ovarian tumours is critical to optimise patient care. The purpose of this study is to evaluate the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) logistic regression model (LR2), ultrasound Simple Rules (SR), the Risk of Malignancy Index (RMI) and subjective assessment (SA) for preoperative characterisation of adnexal masses, when ultrasonography is performed by examiners with different background training and experience., Methods: A 2-year prospective multicentre cross-sectional study. Thirty-five level II ultrasound examiners contributed in three UK hospitals. Transvaginal ultrasonography was performed using a standardised approach. The final outcome was the surgical findings and histological diagnosis. To characterise the adnexal masses, the six-variable prediction model (LR2) with a cutoff of 0.1, the RMI with cutoff of 200, ten SR (five rules for malignancy and five rules for benignity) and SA were applied. The area under the curves (AUCs) for performance of LR2 and RMI were calculated. Diagnostic performance measures for all models assessed were sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and the diagnostic odds ratio (DOR)., Results: Nine-hundred and sixty-two women with adnexal masses underwent transvaginal ultrasonography, whereas 255 had surgery. Prevalence of malignancy was 29% (49 primary invasive epithelial ovarian cancers, 18 borderline ovarian tumours, and 7 metastatic tumours). The AUCs for LR2 and RMI for all masses were 0.94 (95% confidence interval (CI): 0.89-0.97) and 0.90 (95% CI: 0.83-0.94), respectively. In premenopausal women, LR2-RMI difference was 0.09 (95% CI: 0.03-0.15) compared with -0.02 (95% CI: -0.08 to 0.04) in postmenopausal women. For all masses, the DORs for LR2, RMI, SR+SA (using SA when SR inapplicable), SR+MA (assuming malignancy when SR inapplicable), and SA were 62 (95% CI: 27-142), 43 (95% CI: 19-97), 109 (95% CI: 44-274), 66 (95% CI: 27-158), and 70 (95% CI: 30-163), respectively., Conclusion: Overall, the test performance of IOTA prediction models and rules as well as the RMI was maintained in examiners with varying levels of training and experience.

Objective: The identification of novel biomarkers led to the development of the ROMA algorithm incorporating both HE4 and CA125 to predict malignancy in women with a pelvic mass. An ultrasound based prediction model (LR2) developed by the International Ovarian Tumor Analysis (IOTA) study offers better diagnostic performance than CA125 alone. In this study we compared the diagnostic accuracy between LR2 and ROMA., Methods: This study included women with a pelvic mass scheduled for surgery and enrolled in a previous prospective diagnostic accuracy study. Experienced ultrasound examiners, general gynecologists and trainees supervised by one of the experts performed the preoperative transvaginal ultrasound examinations. Serum biomarkers were taken prior to surgery. Accuracy of LR2 and ROMA was estimated at completion of this study and did not form part of the decision making process. Final outcome was histology of removed tissues and surgical stage if relevant., Results: In total 360 women were evaluated. 216 women had benign disease and 144 a malignancy. Overall test performance of LR2 (AUC 0.952) with 94% sensitivity and 82% specificity was significantly better than ROMA (AUC 0.893) with 84% sensitivity and 80% specificity. Difference in AUC was 0.059 (95% CI: 0.026-0.091; P-value 0.0004). Similar results were obtained when stratified for menopausal status., Conclusion: LR2 shows a better diagnostic performance than ROMA for the characterization of a pelvic mass in both pre- and postmenopausal women. These findings suggest that HE4 and CA125 may not play an important role in the diagnosis of ovarian cancer if good quality ultrasonography is available., (Copyright © 2013 Elsevier Inc. All rights reserved.)

In order to ensure that ovarian cancer patients access appropriate treatment to improve the outcome of this disease, accurate characterization before any surgery on ovarian pathology is essential. The International Ovarian Tumor Analysis (IOTA) collaboration has standardized the approach to the ultrasound description of adnexal pathology. A prospectively collected large database enabled previously developed prediction models like the risk of malignancy index (RMI) to be tested and novel prediction models to be developed and externally validated in order to determine the optimal approach to characterize adnexal pathology preoperatively. The main IOTA prediction models (logistic regression model 1 (LR1) and logistic regression model 2 (LR2)) have both shown excellent diagnostic performance (area under the curve (AUC) values of 0.96 and 0.95, respectively) and outperform previous diagnostic algorithms. Their test performance almost matches subjective assessment by experienced examiners, which is accepted to be the best way to classify adnexal masses before surgery. A two-step strategy using the IOTA simple rules supplemented with subjective assessment of ultrasound findings when the rules do not apply, also reached excellent diagnostic performance (sensitivity 90%, specificity 93%) and misclassified fewer malignancies than did the RMI. An evidence-based approach to the preoperative characterization of ovarian and other adnexal masses should include the use of LR1, LR2 or IOTA simple rules and subjective assessment by an experienced examiner., (Copyright © 2013 ISUOG. Published by John Wiley & Sons, Ltd.)

Objectives: To describe clinical and ultrasound features of Brenner tumors of the ovary., Methods: In this retrospective study, the databases of the International Ovarian Tumor Analysis (IOTA) studies and one tertiary center were searched to identify patients who had undergone an ultrasound scan before surgery for an adnexal mass that proved to be a Brenner tumor. Twenty-eight patients with 29 Brenner tumors were included, most of which had been collected within the framework of the IOTA studies. An experienced ultrasound examiner reviewed available ultrasound images (available for 14 tumors), searching for a pattern specific to Brenner tumors., Results: Most patients were postmenopausal and asymptomatic. Twenty-four (83%) tumors were benign, two (7%) were borderline and three (10%) were malignant. Most benign tumors (17/24, 71%) contained solid components and manifested no or minimal blood flow on Doppler examination (19/24, 79%). Information about calcifications was available for 15 benign tumors, and in 13 (87%) calcifications were present. The five borderline and invasively malignant tumors contained solid components less often than did the benign ones (3/5, 60%) and were more richly vascularized on Doppler examination. Information about calcifications was available for four borderline or invasively malignant tumors, and in three (75%) calcifications were present., Conclusion: We failed to demonstrate ultrasound features specific to Brenner tumors. A prospective study is needed to determine if ultrasound features of calcifications can discriminate between Brenner tumors and other types of ovarian tumor., (Copyright © 2012 ISUOG. Published by John Wiley & Sons, Ltd.)

Objective: To compare guidelines from the Royal College of Obstetricians and Gynaecologists (RCOG) based on the Risk of Malignancy Index (RMI) with a protocol based on logistic regression model LR2 developed by the International Ovarian Tumour Analysis (IOTA) group for triaging women with an ovarian mass as low, moderate, or high risk of malignancy., Design and Setting: Observational diagnostic study conducted between 2005 and 2007 at 21 oncology referral centres, referral centres for ultrasonography and general hospitals., Sample: In all, 1938 women undergoing surgery for an ovarian mass., Methods: RCOG guidelines use the RMI to triage women as low (RMI < 25), moderate (25-250), or high (above >250) risk. The IOTA protocol uses LR2s estimated probability of malignancy (<0.05 indicates low risk, ≥ 0.05 but <0.25 moderate risk, and ≥ 0.25 high risk)., Main Outcome Measure: Percentages of benign, borderline and invasive tumours classified as low, moderate or high risk., Results: The IOTA and RCOG protocols classified 71.1% and 62.1% of benign tumours as low risk, respectively (difference 9.0; 95% CI 6.2-11.9, P < 0.0001). Of invasive tumours, 88.6% and 73.6% were labelled high risk (difference 15.0; 10.6-19.4, P < 0.0001), and 3.0% and 5.2% were labelled low risk (difference -2.2; -4.6 to 0.2, P = 0.07) respectively by each protocol. Similar results were found after stratification for menopausal status., Conclusions: The IOTA protocol was more accurate for triage than the RCOG protocol. The IOTA protocol would avoid major surgery for more women with benign tumours while still appropriately referring more women with an invasive tumour to a gynaecological oncologist., (© 2012 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2012 RCOG.)

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.

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., (© 2011 AACR.)

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.

Background: Hitherto, risk prediction models for preoperative ultrasound-based diagnosis of ovarian tumors were dichotomous (benign versus malignant). We develop and validate polytomous models (models that predict more than two events) to diagnose ovarian tumors as benign, borderline, primary invasive or metastatic invasive. The main focus is on how different types of models perform and compare., Methods: A multi-center dataset containing 1066 women was used for model development and internal validation, whilst another multi-center dataset of 1938 women was used for temporal and external validation. Models were based on standard logistic regression and on penalized kernel-based algorithms (least squares support vector machines and kernel logistic regression). We used true polytomous models as well as combinations of dichotomous models based on the 'pairwise coupling' technique to produce polytomous risk estimates. Careful variable selection was performed, based largely on cross-validated c-index estimates. Model performance was assessed with the dichotomous c-index (i.e. the area under the ROC curve) and a polytomous extension, and with calibration graphs., Results: For all models, between 9 and 11 predictors were selected. Internal validation was successful with polytomous c-indexes between 0.64 and 0.69. For the best model dichotomous c-indexes were between 0.73 (primary invasive vs metastatic) and 0.96 (borderline vs metastatic). On temporal and external validation, overall discrimination performance was good with polytomous c-indexes between 0.57 and 0.64. However, discrimination between primary and metastatic invasive tumors decreased to near random levels. Standard logistic regression performed well in comparison with advanced algorithms, and combining dichotomous models performed well in comparison with true polytomous models. The best model was a combination of dichotomous logistic regression models. This model is available online., Conclusions: We have developed models that successfully discriminate between benign, borderline, and invasive ovarian tumors. Methodologically, the combination of dichotomous models was an interesting approach to tackle the polytomous problem. Standard logistic regression models were not outperformed by regularized kernel-based alternatives, a finding to which the careful variable selection procedure will have contributed. The random discrimination between primary and metastatic invasive tumors on temporal/external validation demonstrated once more the necessity of validation studies.

Objectives: 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')., Methods: Patients with adnexal masses, who were put forward by the 19 centers participating in the study, underwent a standardized transvaginal ultrasound examination by a gynecologist or a radiologist specialized in ultrasonography. The examiner prospectively collected information on clinical and ultrasound variables, and classified each mass as benign or malignant on the basis of subjective evaluation of ultrasound findings. The gold standard was the histology of the mass with local clinicians deciding whether to operate on the basis of ultrasound results and the clinical picture. The models' ability to discriminate between malignant and benign masses was assessed, together with the accuracy of the risk estimates., Results: Of the 1938 patients included in the study, 1396 had benign, 373 had primary invasive, 111 had borderline malignant and 58 had metastatic tumors. On external validation (997 patients from 12 centers), the area under the receiver-operating characteristics curve (AUC) for a model containing 12 predictors (LR1) was 0.956, for a reduced model with six predictors (LR2) was 0.949 and for subjective assessment was 0.949. Subjective assessment gave a positive likelihood ratio of 11.0 and a negative likelihood ratio of 0.14. The corresponding likelihood ratios for a previously derived probability threshold (0.1) were 6.84 and 0.09 for LR1, and 6.36 and 0.10 for LR2. On temporal validation (941 patients from seven centers), the AUCs were 0.945 (LR1), 0.918 (LR2) and 0.959 (subjective assessment)., Conclusions: Both models provide excellent discrimination between benign and malignant masses. Because the models provide an objective and reasonably accurate risk estimation, they may improve the management of women with suspected ovarian pathology.

Objective: To determine the sensitivity and specificity of the 'ovarian crescent sign' (OCS)-a rim of normal ovarian tissue seen adjacent to an ipsilateral adnexal mass-as a sonographic feature to discriminate between benign and malignant adnexal masses., Methods: The patients included were a subgroup of patients participating in the International Ovarian Tumor Analysis (IOTA) Phase 2 study, which is an international multicenter study. The subgroup comprised 1938 patients, with an adnexal mass, recruited from 19 ultrasound centers in different countries. All patients were scanned using the same standardized ultrasound protocol. Information on more than 40 demographic and ultrasound variables were collected, but the evaluation of the OCS was optional. Only patients from centers that had evaluated the OCS in > or = 90% of their cases were included. The gold standard was the histological diagnosis of the adnexal mass. The ability of the OCS to discriminate between borderline or invasively malignant vs. benign adnexal masses, as well as between invasively malignant vs. other (benign and borderline) tumors, was determined and compared with the performance of subjective evaluation of ultrasound findings by the ultrasound examiner., Results: The OCS was evaluated in 1377 adnexal masses from 12 centers, 938 (68%) masses being benign, 86 (6%) borderline, 305 (22%) primary invasive and 48 (3%) metastases. The OCS was present in 398 (42%) of 938 benign masses, in 14 (16%) of 86 borderline tumors, in 18 (6%) of 305 primary invasive tumors (one malignant struma ovarii, one uterine clear cell adenocarcinoma and 16 epithelial carcinomas, i.e. four Stage I and 12 Stage II-IV) and in two (4%) of 48 ovarian metastases. Hence, the sensitivity and specificity for absent OCS to identify a malignancy was 92% and 42%, respectively, and the positive and negative likelihood ratios (LR+ and LR-, respectively) were 1.60 and 0.18. Subjective impression performed significantly better than the OCS. Sensitivity and specificity were 90% and 92%, respectively, LR+ was 11.0 and LR- was 0.10. For discrimination between invasive vs. benign or borderline tumors, the sensitivity for absent OCS was 94%, the specificity was 40%, the LR+ was 1.58 and the LR- was 0.14., Conclusion: This study confirms previous reports that the presence of the OCS decreases the likelihood of invasive malignancy in adnexal masses. However it is a poor discriminator between benign and malignant adnexal masses., (Copyright 2010 ISUOG. Published by John Wiley & Sons, Ltd.)