External Validation of O-RADS US Risk Stratification and Management                     System

Hack, Kalesha; Gandhi, Niket; Bouchard-Fortier, Geneviève; Chawla, Tanya; Ferguson, Sarah E; Li, Siying; Kahn, Daniel; Tyrrell, Pascal N.; Glanc, Phyllis

doi:10.1148/radiol.211868

Cited by 41 publications

(47 citation statements)

References 21 publications

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“…After full-text reading, three papers were excluded (no data for constructing 2 × 2 table available (n = 2), and use of MRI, instead of ultrasound (n = 1)). Eleven papers were ultimately included in the qualitative and quantitative synthesis [22][23][24][25][26][27][28][29][30][31][32]. A flowchart summarizing the literature search is shown in Figure 1.…”

Section: Search Resultsmentioning

confidence: 99%

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

“…Concerning the domain "index test", all studies adequately described the method of the index text, as well as how it was performed and interpreted. Ten studies used IOTA terminology of the mass features [22,23,[25][26][27][28][29][30][31][32], while one used the ADNEX model [24]. In all retrospective studies, examiners were blinded to the reference standard result.…”

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

“…The study design was retrospective in 10 studies [22][23][24][25][26][27][29][30][31][32] and prospective in just one study [28]. Eight studies were considered as having high risk regarding the patient selection domain, since inappropriate exclusions (for example, cases with poor image quality or cases with not all data available) were observed [22,23,25,[27][28][29][30][31][32], and one study was unclear since a complete description of the exclusion criteria was lacking [26] Concerning the domain "index test", all studies adequately described the method of the index text, as well as how it was performed and interpreted. Ten studies used IOTA terminology of the mass features [22,23,[25][26][27][28][29][30][31][32], while one used the ADNEX model [24].…”

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

“…Out of these 4634 adnexal masses, 1404 were malignancies (including 268 borderline tumors, 1058 primary ovarian cancers, and 78 metastatic cancers). In one study, four cases were considered as malignant for the final outcome on the basis of tumor growth during surveillance, but no histology was reported (30). According to histology, primary cancers were distributed as epithelial carcinomas (n = 829), nonepithelial tumors (n = 94), and "other malignant primary malignant lesions (n = 131).…”

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

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Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis

Vara

Manzour

Chacón

et al. 2022

Cancers

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In this systematic review and meta-analysis, we aimed to assess the pooled diagnostic performance of the so-called Ovarian Adnexal Report Data System (O-RADS) for classifying adnexal masses using transvaginal ultrasound, a classification system that was introduced in 2020. We performed a search for studies reporting the use of the O-RADS system for classifying adnexal masses from January 2020 to April 2022 in several databases (Medline (PubMed), Google Scholar, Scopus, Cochrane, and Web of Science). We selected prospective and retrospective cohort studies using the O-RADS system for classifying adnexal masses with histologic diagnosis or conservative management demonstrating spontaneous resolution or persistence in cases of benign appearing masses after follow-up scan as the reference standard. We excluded studies not related to the topic under review, studies not addressing O-RADS classification, studies addressing MRI O-RADS classification, letters to the editor, commentaries, narrative reviews, consensus documents, and studies where data were not available for constructing a 2 × 2 table. The pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated. The quality of the studies was evaluated using QUADAS-2. A total of 502 citations were identified. Ultimately, 11 studies comprising 4634 masses were included. The mean prevalence of ovarian malignancy was 32%. The risk of bias was high in eight studies for the “patient selection” domain. The risk of bias was low for the “index test” and “reference test” domains for all studies. Overall, the pooled estimated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and DOR of the O-RADS system for classifying adnexal masses were 97% (95% confidence interval (CI) = 94%–98%), 77% (95% CI = 68%–84%), 4.2 (95% CI = 2.9–6.0), 0.04 (95% CI = 0.03–0.07), and 96 (95% CI = 50–185), respectively. Heterogeneity was moderate for sensitivity and high for specificity. In conclusion, the O-RADS system has good sensitivity and moderate specificity for classifying adnexal masses.

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Section: Search Resultsmentioning

confidence: 99%

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

See 3 more Smart Citations

Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis

Vara

Manzour

Chacón

et al. 2022

Cancers

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Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort

et al. 2023

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ImportanceUltrasonography-based risk models can help nonexpert clinicians evaluate adnexal lesions and reduce surgical interventions for benign tumors. Yet, these models have limited uptake in the US, and studies comparing their diagnostic accuracy are lacking.ObjectiveTo evaluate, in a US cohort, the diagnostic performance of 3 ultrasonography-based risk models for differentiating between benign and malignant adnexal lesions: International Ovarian Tumor Analysis (IOTA) Simple Rules with inconclusive cases reclassified as malignant or reevaluated by an expert, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX), and Ovarian-Adnexal Reporting and Data System (O-RADS).Design, Setting, and ParticipantsThis retrospective diagnostic study was conducted at a single US academic medical center and included consecutive patients aged 18 to 89 years with adnexal masses that were managed surgically or conservatively between January 2017 and October 2022.ExposureEvaluation of adnexal lesions using the Simple Rules, ADNEX, and O-RADS.Main Outcomes and MeasuresThe main outcome was diagnostic performance, including area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Surgery or follow-up were reference standards. Secondary analyses evaluated the models’ performances stratified by menopause status and race.ResultsThe cohort included 511 female patients with a 15.9% malignant tumor prevalence (81 patients). Mean (SD) ages of patients with benign and malignant adnexal lesions were 44.1 (14.4) and 52.5 (15.2) years, respectively, and 200 (39.1%) were postmenopausal. In the ROC analysis, the AUCs for discriminative performance of the ADNEX and O-RADS models were 0.96 (95% CI, 0.93-0.98) and 0.92 (95% CI, 0.90-0.95), respectively. After converting the ADNEX continuous individualized risk into the discrete ordinal categories of O-RADS, the ADNEX performance was reduced to an AUC of 0.93 (95% CI, 0.90-0.96), which was similar to that for O-RADS. The Simple Rules combined with expert reevaluation had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 91.9% specificity (95% CI, 88.9%-94.3%), and the Simple Rules combined with malignant classification had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 88.1% specificity (95% CI, 84.7%-91.0%). At a 10% risk threshold, ADNEX had 91.4% sensitivity (95% CI, 83.0%-96.5%) and 86.3% specificity (95% CI, 82.7%-89.4%) and O-RADS had 98.8% sensitivity (95% CI, 93.3%-100%) and 74.4% specificity (95% CI, 70.0%-78.5%). The specificities of all models were significantly lower in the postmenopausal group. Subgroup analysis revealed high performances independent of race.Conclusions and RelevanceIn this diagnostic study of a US cohort, the Simple Rules, ADNEX, and O-RADS models performed well in differentiating between benign and malignant adnexal lesions; this outcome has been previously reported primarily in European populations. Risk stratification models can lead to more accurate and consistent evaluations of adnexal masses, especially when used by nonexpert clinicians, and may reduce unnecessary surgeries.

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External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups

et al. 2023

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ImportanceCorrect 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.ObjectiveTo investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy.Design, Setting, and ParticipantsRetrospective 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.ExposuresStratification into O-RADS categories (malignancy risk &lt;1%, 1% to &lt;10%, 10% to &lt;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 MeasuresObserved 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.ResultsMedian 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 RelevanceThe 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%.

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External Validation of O-RADS US Risk Stratification and Management System

Cited by 41 publications

References 21 publications

Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis

Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis

Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort

External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups

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