Cargando…
Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort
IMPORTANCE: Ultrasonography-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. OBJECTIVE: To evaluate, in a US coho...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346125/ https://www.ncbi.nlm.nih.gov/pubmed/37440228 http://dx.doi.org/10.1001/jamanetworkopen.2023.23289 |
_version_ | 1785073240617517056 |
---|---|
author | Yoeli-Bik, Roni Longman, Ryan E. Wroblewski, Kristen Weigert, Melanie Abramowicz, Jacques S. Lengyel, Ernst |
author_facet | Yoeli-Bik, Roni Longman, Ryan E. Wroblewski, Kristen Weigert, Melanie Abramowicz, Jacques S. Lengyel, Ernst |
author_sort | Yoeli-Bik, Roni |
collection | PubMed |
description | IMPORTANCE: Ultrasonography-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. OBJECTIVE: To 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 PARTICIPANTS: This 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. EXPOSURE: Evaluation of adnexal lesions using the Simple Rules, ADNEX, and O-RADS. MAIN OUTCOMES AND MEASURES: The 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. RESULTS: The 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 RELEVANCE: In 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. |
format | Online Article Text |
id | pubmed-10346125 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Medical Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-103461252023-07-15 Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort Yoeli-Bik, Roni Longman, Ryan E. Wroblewski, Kristen Weigert, Melanie Abramowicz, Jacques S. Lengyel, Ernst JAMA Netw Open Original Investigation IMPORTANCE: Ultrasonography-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. OBJECTIVE: To 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 PARTICIPANTS: This 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. EXPOSURE: Evaluation of adnexal lesions using the Simple Rules, ADNEX, and O-RADS. MAIN OUTCOMES AND MEASURES: The 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. RESULTS: The 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 RELEVANCE: In 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. American Medical Association 2023-07-13 /pmc/articles/PMC10346125/ /pubmed/37440228 http://dx.doi.org/10.1001/jamanetworkopen.2023.23289 Text en Copyright 2023 Yoeli-Bik R et al. JAMA Network Open. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the CC-BY License. |
spellingShingle | Original Investigation Yoeli-Bik, Roni Longman, Ryan E. Wroblewski, Kristen Weigert, Melanie Abramowicz, Jacques S. Lengyel, Ernst Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort |
title | Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort |
title_full | Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort |
title_fullStr | Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort |
title_full_unstemmed | Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort |
title_short | Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort |
title_sort | diagnostic performance of ultrasonography-based risk models in differentiating between benign and malignant ovarian tumors in a us cohort |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346125/ https://www.ncbi.nlm.nih.gov/pubmed/37440228 http://dx.doi.org/10.1001/jamanetworkopen.2023.23289 |
work_keys_str_mv | AT yoelibikroni diagnosticperformanceofultrasonographybasedriskmodelsindifferentiatingbetweenbenignandmalignantovariantumorsinauscohort AT longmanryane diagnosticperformanceofultrasonographybasedriskmodelsindifferentiatingbetweenbenignandmalignantovariantumorsinauscohort AT wroblewskikristen diagnosticperformanceofultrasonographybasedriskmodelsindifferentiatingbetweenbenignandmalignantovariantumorsinauscohort AT weigertmelanie diagnosticperformanceofultrasonographybasedriskmodelsindifferentiatingbetweenbenignandmalignantovariantumorsinauscohort AT abramowiczjacquess diagnosticperformanceofultrasonographybasedriskmodelsindifferentiatingbetweenbenignandmalignantovariantumorsinauscohort AT lengyelernst diagnosticperformanceofultrasonographybasedriskmodelsindifferentiatingbetweenbenignandmalignantovariantumorsinauscohort |