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Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses

AIM: This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of ad...

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Autores principales: Qian, Le, Du, Qinwen, Jiang, Meijiao, Yuan, Fei, Chen, Hui, Feng, Weiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204044/
https://www.ncbi.nlm.nih.gov/pubmed/34141619
http://dx.doi.org/10.3389/fonc.2021.673722
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author Qian, Le
Du, Qinwen
Jiang, Meijiao
Yuan, Fei
Chen, Hui
Feng, Weiwei
author_facet Qian, Le
Du, Qinwen
Jiang, Meijiao
Yuan, Fei
Chen, Hui
Feng, Weiwei
author_sort Qian, Le
collection PubMed
description AIM: This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass. METHODS: This single-centre diagnostic accuracy study involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied. Pathology was the clinical reference standard. The diagnostic performances of prediction models were measured by evaluating receiver-operating characteristic curves, sensitivities, specificities, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic odds ratios. RESULTS: To discriminate benign and malignant tumors, areas under the ROC curves (AUCs) for ADNEX models were 0.94 (95% CI: 0.92–0.96) with CA125 and 0.94 (95% CI: 0.91–0.96) without CA125, which were significantly higher than the AUCs for RMI I-III: 0.87 (95% CI: 0.83–0.90), 0.83 (95% CI: 0.80–0.86), and 0.82 (95% CI: 0.78–0.86), (all P < 0.0001). At a cut-off of 10%, the ADNEX model with CA125 had the highest sensitivity (0.93; 95% CI: 0.87–0.97) compared with the other models. The SRs model achieved a sensitivity of 0.93 (95% CI: 0.86–0.97) and a specificity of 0.86 (95% CI: 0.82–0.89) when inconclusive diagnoses (11.7%) were classified as malignant. CONCLUSION: ADNEX and SRs models were excellent at characterising adnexal masses which were superior to the RMI in Chinese patients.
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spelling pubmed-82040442021-06-16 Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses Qian, Le Du, Qinwen Jiang, Meijiao Yuan, Fei Chen, Hui Feng, Weiwei Front Oncol Oncology AIM: This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass. METHODS: This single-centre diagnostic accuracy study involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied. Pathology was the clinical reference standard. The diagnostic performances of prediction models were measured by evaluating receiver-operating characteristic curves, sensitivities, specificities, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic odds ratios. RESULTS: To discriminate benign and malignant tumors, areas under the ROC curves (AUCs) for ADNEX models were 0.94 (95% CI: 0.92–0.96) with CA125 and 0.94 (95% CI: 0.91–0.96) without CA125, which were significantly higher than the AUCs for RMI I-III: 0.87 (95% CI: 0.83–0.90), 0.83 (95% CI: 0.80–0.86), and 0.82 (95% CI: 0.78–0.86), (all P < 0.0001). At a cut-off of 10%, the ADNEX model with CA125 had the highest sensitivity (0.93; 95% CI: 0.87–0.97) compared with the other models. The SRs model achieved a sensitivity of 0.93 (95% CI: 0.86–0.97) and a specificity of 0.86 (95% CI: 0.82–0.89) when inconclusive diagnoses (11.7%) were classified as malignant. CONCLUSION: ADNEX and SRs models were excellent at characterising adnexal masses which were superior to the RMI in Chinese patients. Frontiers Media S.A. 2021-06-01 /pmc/articles/PMC8204044/ /pubmed/34141619 http://dx.doi.org/10.3389/fonc.2021.673722 Text en Copyright © 2021 Qian, Du, Jiang, Yuan, Chen and Feng https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Qian, Le
Du, Qinwen
Jiang, Meijiao
Yuan, Fei
Chen, Hui
Feng, Weiwei
Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses
title Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses
title_full Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses
title_fullStr Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses
title_full_unstemmed Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses
title_short Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses
title_sort comparison of the diagnostic performances of ultrasound-based models for predicting malignancy in patients with adnexal masses
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204044/
https://www.ncbi.nlm.nih.gov/pubmed/34141619
http://dx.doi.org/10.3389/fonc.2021.673722
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