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Prediction of lymphovascular space invasion in patients with endometrial cancer
Objective: Predict the presence of lymphovascular space invasion (LVSI), using uterine factors such as tumor diameter (TD), grade, and depth of myometrial invasion (MMI). Develop a predictive model that could serve as a marker of LVSI in women with endometrial cancer (EC). Methods: Data from 888 pat...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8241765/ https://www.ncbi.nlm.nih.gov/pubmed/34220310 http://dx.doi.org/10.7150/ijms.60718 |
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author | Kim, Sang Il Yoon, Joo Hee Lee, Sung Jong Song, Min Jong Kim, Jin Hwi Lee, Hae Nam Jung, Gyul Yoo, Ji Geun |
author_facet | Kim, Sang Il Yoon, Joo Hee Lee, Sung Jong Song, Min Jong Kim, Jin Hwi Lee, Hae Nam Jung, Gyul Yoo, Ji Geun |
author_sort | Kim, Sang Il |
collection | PubMed |
description | Objective: Predict the presence of lymphovascular space invasion (LVSI), using uterine factors such as tumor diameter (TD), grade, and depth of myometrial invasion (MMI). Develop a predictive model that could serve as a marker of LVSI in women with endometrial cancer (EC). Methods: Data from 888 patients with endometrioid EC who were treated between January 2009 and December 2018 were reviewed. The patients' data were retrieved from six institutions. We assessed the differences in the clinicopathological characteristics between patients with and without LVSI. We performed logistic regression analysis to determine which clinicopathological characteristics were the risk factors for positive LVSI status and to estimate the odds ratio (OR) for each covariate. Using the risk factors and OR identified through this process, we created a model that could predict LVSI and analyzed it further using receiver operating characteristic curve analysis. Results: In multivariate logistic regression analysis, tumor size (P = 0.027), percentage of MMI (P < 0.001), and presence of cervical stromal invasion (P = 0.002) were identified as the risk factors for LVSI. Based on the results of multivariate logistic regression analysis, we developed a simplified LVSI prediction model for clinical use. We defined the “LVSI index” as “TD×%MMI×tumor grade×cervical stromal involvement.” The area under curve was 0.839 (95% CI= 0.809-0.869; sensitivity, 74.1%; specificity, 80.5%; negative predictive value, 47.3%; positive predictive value, 8.6%; P < 0.001), and the optimal cut-off value was 200. Conclusion: Using the modified risk index of LVSI, it is possible to predict the presence of LVSI in women with endometrioid endometrial cancer. Our prediction model may be an appropriate tool for integration into the clinical decision-making process when assessed either preoperatively or intraoperatively. |
format | Online Article Text |
id | pubmed-8241765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-82417652021-07-01 Prediction of lymphovascular space invasion in patients with endometrial cancer Kim, Sang Il Yoon, Joo Hee Lee, Sung Jong Song, Min Jong Kim, Jin Hwi Lee, Hae Nam Jung, Gyul Yoo, Ji Geun Int J Med Sci Research Paper Objective: Predict the presence of lymphovascular space invasion (LVSI), using uterine factors such as tumor diameter (TD), grade, and depth of myometrial invasion (MMI). Develop a predictive model that could serve as a marker of LVSI in women with endometrial cancer (EC). Methods: Data from 888 patients with endometrioid EC who were treated between January 2009 and December 2018 were reviewed. The patients' data were retrieved from six institutions. We assessed the differences in the clinicopathological characteristics between patients with and without LVSI. We performed logistic regression analysis to determine which clinicopathological characteristics were the risk factors for positive LVSI status and to estimate the odds ratio (OR) for each covariate. Using the risk factors and OR identified through this process, we created a model that could predict LVSI and analyzed it further using receiver operating characteristic curve analysis. Results: In multivariate logistic regression analysis, tumor size (P = 0.027), percentage of MMI (P < 0.001), and presence of cervical stromal invasion (P = 0.002) were identified as the risk factors for LVSI. Based on the results of multivariate logistic regression analysis, we developed a simplified LVSI prediction model for clinical use. We defined the “LVSI index” as “TD×%MMI×tumor grade×cervical stromal involvement.” The area under curve was 0.839 (95% CI= 0.809-0.869; sensitivity, 74.1%; specificity, 80.5%; negative predictive value, 47.3%; positive predictive value, 8.6%; P < 0.001), and the optimal cut-off value was 200. Conclusion: Using the modified risk index of LVSI, it is possible to predict the presence of LVSI in women with endometrioid endometrial cancer. Our prediction model may be an appropriate tool for integration into the clinical decision-making process when assessed either preoperatively or intraoperatively. Ivyspring International Publisher 2021-06-01 /pmc/articles/PMC8241765/ /pubmed/34220310 http://dx.doi.org/10.7150/ijms.60718 Text en © The author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Research Paper Kim, Sang Il Yoon, Joo Hee Lee, Sung Jong Song, Min Jong Kim, Jin Hwi Lee, Hae Nam Jung, Gyul Yoo, Ji Geun Prediction of lymphovascular space invasion in patients with endometrial cancer |
title | Prediction of lymphovascular space invasion in patients with endometrial cancer |
title_full | Prediction of lymphovascular space invasion in patients with endometrial cancer |
title_fullStr | Prediction of lymphovascular space invasion in patients with endometrial cancer |
title_full_unstemmed | Prediction of lymphovascular space invasion in patients with endometrial cancer |
title_short | Prediction of lymphovascular space invasion in patients with endometrial cancer |
title_sort | prediction of lymphovascular space invasion in patients with endometrial cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8241765/ https://www.ncbi.nlm.nih.gov/pubmed/34220310 http://dx.doi.org/10.7150/ijms.60718 |
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