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A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index
SIMPLE SUMMARY: Ovarian Endometrioma (OE) is a precancerous condition for endometriosis-associated ovarian cancer (EAOC). For many clinicians observing OE outpatients, setting the appropriate time for surgery can be a challenge because there is no suggestive milestone. Out of the fear of malignant t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345171/ https://www.ncbi.nlm.nih.gov/pubmed/34359728 http://dx.doi.org/10.3390/cancers13153829 |
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author | Kawahara, Naoki Miyake, Ryuta Yamanaka, Shoichiro Kobayashi, Hiroshi |
author_facet | Kawahara, Naoki Miyake, Ryuta Yamanaka, Shoichiro Kobayashi, Hiroshi |
author_sort | Kawahara, Naoki |
collection | PubMed |
description | SIMPLE SUMMARY: Ovarian Endometrioma (OE) is a precancerous condition for endometriosis-associated ovarian cancer (EAOC). For many clinicians observing OE outpatients, setting the appropriate time for surgery can be a challenge because there is no suggestive milestone. Out of the fear of malignant transformation, many patients have surgery conducted according to respective faculty standards. This study aims to investigate a novel, noninvasive method not requiring an MRI device. This study partly helps to lift the above restrictions, and has the potential to suggest intervention-appropriate timing to the physician. ABSTRACT: Background: Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate between ovarian endometrioma (OE) and endometriosis-associated ovarian cancer (EAOC), with a sensitivity and specificity of 86% and 94%, respectively. MRI models that can measure R2 values are limited, and the R2 values differ between MRI models. This study aims to extract the factors contributing to the R2 value, and to make a formula for estimating the R2 values, and to assess whether the R2 predictive index calculated by the formula could discriminate EAOC from OE. Methods: This retrospective study was conducted at our institution from November 2012 to February 2019. A total of 247 patients were included in this study. Patients with benign ovarian tumors mainly received laparoscopic surgery, and the patients suspected of having malignant tumors underwent laparotomy. Information from a chart review of the patients’ medical records was collected. Results: In the investigative cohort, among potential factors correlated with the R2 value, multiple regression analyses revealed that tumor diameter and CEA could predict the R2 value. In the validation cohort, multivariate analysis confirmed that age, CRP, and the R2 predictive index were the independent factors. Conclusions: The R2 predictive index is useful and valuable to the detection of the malignant transformation of endometrioma. |
format | Online Article Text |
id | pubmed-8345171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83451712021-08-07 A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index Kawahara, Naoki Miyake, Ryuta Yamanaka, Shoichiro Kobayashi, Hiroshi Cancers (Basel) Article SIMPLE SUMMARY: Ovarian Endometrioma (OE) is a precancerous condition for endometriosis-associated ovarian cancer (EAOC). For many clinicians observing OE outpatients, setting the appropriate time for surgery can be a challenge because there is no suggestive milestone. Out of the fear of malignant transformation, many patients have surgery conducted according to respective faculty standards. This study aims to investigate a novel, noninvasive method not requiring an MRI device. This study partly helps to lift the above restrictions, and has the potential to suggest intervention-appropriate timing to the physician. ABSTRACT: Background: Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate between ovarian endometrioma (OE) and endometriosis-associated ovarian cancer (EAOC), with a sensitivity and specificity of 86% and 94%, respectively. MRI models that can measure R2 values are limited, and the R2 values differ between MRI models. This study aims to extract the factors contributing to the R2 value, and to make a formula for estimating the R2 values, and to assess whether the R2 predictive index calculated by the formula could discriminate EAOC from OE. Methods: This retrospective study was conducted at our institution from November 2012 to February 2019. A total of 247 patients were included in this study. Patients with benign ovarian tumors mainly received laparoscopic surgery, and the patients suspected of having malignant tumors underwent laparotomy. Information from a chart review of the patients’ medical records was collected. Results: In the investigative cohort, among potential factors correlated with the R2 value, multiple regression analyses revealed that tumor diameter and CEA could predict the R2 value. In the validation cohort, multivariate analysis confirmed that age, CRP, and the R2 predictive index were the independent factors. Conclusions: The R2 predictive index is useful and valuable to the detection of the malignant transformation of endometrioma. MDPI 2021-07-29 /pmc/articles/PMC8345171/ /pubmed/34359728 http://dx.doi.org/10.3390/cancers13153829 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kawahara, Naoki Miyake, Ryuta Yamanaka, Shoichiro Kobayashi, Hiroshi A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
title | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
title_full | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
title_fullStr | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
title_full_unstemmed | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
title_short | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
title_sort | novel predictive tool for discriminating endometriosis associated ovarian cancer from ovarian endometrioma: the r2 predictive index |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345171/ https://www.ncbi.nlm.nih.gov/pubmed/34359728 http://dx.doi.org/10.3390/cancers13153829 |
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