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Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study

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 mode...

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Autores principales: Sayasneh, A, Ferrara, L, De Cock, B, Saso, S, Al-Memar, M, Johnson, S, Kaijser, J, Carvalho, J, Husicka, R, Smith, A, Stalder, C, Blanco, M C, Ettore, G, Van Calster, B, Timmerman, D, Bourne, T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997550/
https://www.ncbi.nlm.nih.gov/pubmed/27482647
http://dx.doi.org/10.1038/bjc.2016.227
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author Sayasneh, A
Ferrara, L
De Cock, B
Saso, S
Al-Memar, M
Johnson, S
Kaijser, J
Carvalho, J
Husicka, R
Smith, A
Stalder, C
Blanco, M C
Ettore, G
Van Calster, B
Timmerman, D
Bourne, T
author_facet Sayasneh, A
Ferrara, L
De Cock, B
Saso, S
Al-Memar, M
Johnson, S
Kaijser, J
Carvalho, J
Husicka, R
Smith, A
Stalder, C
Blanco, M C
Ettore, G
Van Calster, B
Timmerman, D
Bourne, T
author_sort Sayasneh, A
collection PubMed
description 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.
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spelling pubmed-49975502017-08-23 Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study Sayasneh, A Ferrara, L De Cock, B Saso, S Al-Memar, M Johnson, S Kaijser, J Carvalho, J Husicka, R Smith, A Stalder, C Blanco, M C Ettore, G Van Calster, B Timmerman, D Bourne, T Br J Cancer Clinical Study 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. Nature Publishing Group 2016-08-23 2016-08-02 /pmc/articles/PMC4997550/ /pubmed/27482647 http://dx.doi.org/10.1038/bjc.2016.227 Text en Copyright © 2016 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Clinical Study
Sayasneh, A
Ferrara, L
De Cock, B
Saso, S
Al-Memar, M
Johnson, S
Kaijser, J
Carvalho, J
Husicka, R
Smith, A
Stalder, C
Blanco, M C
Ettore, G
Van Calster, B
Timmerman, D
Bourne, T
Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study
title Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study
title_full Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study
title_fullStr Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study
title_full_unstemmed Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study
title_short Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study
title_sort evaluating the risk of ovarian cancer before surgery using the adnex model: a multicentre external validation study
topic Clinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997550/
https://www.ncbi.nlm.nih.gov/pubmed/27482647
http://dx.doi.org/10.1038/bjc.2016.227
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