open access

Vol 88, No 12 (2017)
Research paper
Published online: 2017-12-29
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The use of sonographic subjective tumor assessment, IOTA logistic regression model 1, IOTA Simple Rules and GI-RADS system in the preoperative prediction of malignancy in women with adnexal masses

Jarosław Koneczny1, Artur Czekierdowski2, Marek Florczak1, Paweł Poziemski1, Norbert Stachowicz3, Dariusz Borowski4
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Pubmed: 29303221
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Ginekol Pol 2017;88(12):647-653.
Affiliations
  1. Department of Obstetrics and Gynecology, County Hospital, Minsk Mazowiecki, Poland
  2. Department of Gynecologic Oncology and Gynecology of the Medical University of Lublin, Poland
  3. Department of Epidemiology and Clinical Research Methodology, Medical University of Lublin, Poland
  4. Department of Obstetrics and Gynecology, Collegium Medicum, Nicolaus Copernicus University in Toruń, ul.Jagiellońska 13-15, 85-067 Bydgoszcz

open access

Vol 88, No 12 (2017)
ORIGINAL PAPERS Gynecology
Published online: 2017-12-29

Abstract

Background: Sonography based methods with various tumor markers are currently used to discriminate the type of adnexal masses. Objective: To compare the predictive value of selected sonography-based models along with subjective assessment in ovarian cancer prediction. Material and methods: We analyzed data of 271 women operated because of adnexal masses. All masses were verified by histological examination. Preoperative sonography was performed in all patients and various predictive models includ¬ing IOTA group logistic regression model LR1 (LR1), IOTA simple ultrasound-based rules by IOTA (SR), GI-RADS and risk of malignancy index (RMI3) were used. ROC curves were constructed and respective AUC’s with 95% CI’s were compared. Results: Of 271 masses 78 proved to be malignant including 6 borderline tumors. LR1 had sensitivity of 91.0%, specificity of 91.2%, AUC = 0.95 (95% CI: 0.92–0.98). Sensitivity for GI-RADS for 271 patients was 88.5% with specificity of 85% and AUC = 0.91 (95% CI: 0.88–0.95). Subjective assessment yielded sensitivity and specificity of 85.9% and 96.9%, respectively with AUC = 0.97 (95% CI: 0.94–0.99). SR were applicable in 236 masses and had sensitivity of 90.6% with specificity of 95.3% and AUC = 0.93 (95% CI 0.89–0.97). RMI3 was calculated only in 104 women who had CA125 available and had sensitivity of 55.3%, specificity of 94% and AUC = 0.85 (95% CI: 0.77–0.93). Conclusions: Although subjective assessment by the ultrasound expert remains the best current method of adnexal tumors preoperative discrimination, the simplicity and high predictive value favor the IOTA SR method, and when not applicable, the IOTA LR1 or GI-RADS models to be primarily and effectively used.

Abstract

Background: Sonography based methods with various tumor markers are currently used to discriminate the type of adnexal masses. Objective: To compare the predictive value of selected sonography-based models along with subjective assessment in ovarian cancer prediction. Material and methods: We analyzed data of 271 women operated because of adnexal masses. All masses were verified by histological examination. Preoperative sonography was performed in all patients and various predictive models includ¬ing IOTA group logistic regression model LR1 (LR1), IOTA simple ultrasound-based rules by IOTA (SR), GI-RADS and risk of malignancy index (RMI3) were used. ROC curves were constructed and respective AUC’s with 95% CI’s were compared. Results: Of 271 masses 78 proved to be malignant including 6 borderline tumors. LR1 had sensitivity of 91.0%, specificity of 91.2%, AUC = 0.95 (95% CI: 0.92–0.98). Sensitivity for GI-RADS for 271 patients was 88.5% with specificity of 85% and AUC = 0.91 (95% CI: 0.88–0.95). Subjective assessment yielded sensitivity and specificity of 85.9% and 96.9%, respectively with AUC = 0.97 (95% CI: 0.94–0.99). SR were applicable in 236 masses and had sensitivity of 90.6% with specificity of 95.3% and AUC = 0.93 (95% CI 0.89–0.97). RMI3 was calculated only in 104 women who had CA125 available and had sensitivity of 55.3%, specificity of 94% and AUC = 0.85 (95% CI: 0.77–0.93). Conclusions: Although subjective assessment by the ultrasound expert remains the best current method of adnexal tumors preoperative discrimination, the simplicity and high predictive value favor the IOTA SR method, and when not applicable, the IOTA LR1 or GI-RADS models to be primarily and effectively used.
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Keywords

ovarian cancer prediction, sonography, IOTA group, Simple Rules, LR1 model, GI-RADS model, RMI model

About this article
Title

The use of sonographic subjective tumor assessment, IOTA logistic regression model 1, IOTA Simple Rules and GI-RADS system in the preoperative prediction of malignancy in women with adnexal masses

Journal

Ginekologia Polska

Issue

Vol 88, No 12 (2017)

Article type

Research paper

Pages

647-653

Published online

2017-12-29

Page views

2518

Article views/downloads

4026

DOI

10.5603/GP.a2017.0116

Pubmed

29303221

Bibliographic record

Ginekol Pol 2017;88(12):647-653.

Keywords

ovarian cancer prediction
sonography
IOTA group
Simple Rules
LR1 model
GI-RADS model
RMI model

Authors

Jarosław Koneczny
Artur Czekierdowski
Marek Florczak
Paweł Poziemski
Norbert Stachowicz
Dariusz Borowski

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