Cargando…
A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients
OBJECTIVE: This study investigated site-specific differences in clinical factors for recurrence in patients who were newly diagnosed and treated for endometrial cancer. A model for predicting recurrence sites was generated. METHODS: Electronic medical records’ data were retrieved from January 2006 t...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620664/ https://www.ncbi.nlm.nih.gov/pubmed/36316771 http://dx.doi.org/10.1186/s12885-022-10193-3 |
_version_ | 1784821374687117312 |
---|---|
author | Shin, Wonkyo Yang, Seong J. Park, Sang-Yoon Kang, Sokbom Lee, Dong Ock Lim, Myong Cheol Seo, Sang-Soo |
author_facet | Shin, Wonkyo Yang, Seong J. Park, Sang-Yoon Kang, Sokbom Lee, Dong Ock Lim, Myong Cheol Seo, Sang-Soo |
author_sort | Shin, Wonkyo |
collection | PubMed |
description | OBJECTIVE: This study investigated site-specific differences in clinical factors for recurrence in patients who were newly diagnosed and treated for endometrial cancer. A model for predicting recurrence sites was generated. METHODS: Electronic medical records’ data were retrieved from January 2006 to December 2018 for patients who were diagnosed with endometrial cancer at the National cancer center in Korea. Recurrence sites were classified as local, regional, or distant. We used multinomial logistic regression models that modeled the log-odds for the three recurrence sites relative to non-recurrence as a linear combination of possible risk factors for the recurrence of endometrial cancer. RESULTS: The data of 611 patients were selected for analysis; there were 20, 12, and 25 cases of local, regional, and distant recurrence, respectively, and 554 patients had no recurrence. High-grade disease was associated with local recurrence; non-endometrioid histology and parametrial invasion were risk factors for regional recurrence; additionally, parametrial invasion and no lymphadenectomy were associated with distant metastasis. CONCLUSION: We identified different risk factors specific for each type of recurrence site. Using these risk factors, we suggest that individually tailored adjuvant treatments be introduced for patients. |
format | Online Article Text |
id | pubmed-9620664 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96206642022-11-01 A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients Shin, Wonkyo Yang, Seong J. Park, Sang-Yoon Kang, Sokbom Lee, Dong Ock Lim, Myong Cheol Seo, Sang-Soo BMC Cancer Research OBJECTIVE: This study investigated site-specific differences in clinical factors for recurrence in patients who were newly diagnosed and treated for endometrial cancer. A model for predicting recurrence sites was generated. METHODS: Electronic medical records’ data were retrieved from January 2006 to December 2018 for patients who were diagnosed with endometrial cancer at the National cancer center in Korea. Recurrence sites were classified as local, regional, or distant. We used multinomial logistic regression models that modeled the log-odds for the three recurrence sites relative to non-recurrence as a linear combination of possible risk factors for the recurrence of endometrial cancer. RESULTS: The data of 611 patients were selected for analysis; there were 20, 12, and 25 cases of local, regional, and distant recurrence, respectively, and 554 patients had no recurrence. High-grade disease was associated with local recurrence; non-endometrioid histology and parametrial invasion were risk factors for regional recurrence; additionally, parametrial invasion and no lymphadenectomy were associated with distant metastasis. CONCLUSION: We identified different risk factors specific for each type of recurrence site. Using these risk factors, we suggest that individually tailored adjuvant treatments be introduced for patients. BioMed Central 2022-10-31 /pmc/articles/PMC9620664/ /pubmed/36316771 http://dx.doi.org/10.1186/s12885-022-10193-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Shin, Wonkyo Yang, Seong J. Park, Sang-Yoon Kang, Sokbom Lee, Dong Ock Lim, Myong Cheol Seo, Sang-Soo A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
title | A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
title_full | A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
title_fullStr | A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
title_full_unstemmed | A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
title_short | A predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
title_sort | predictive model based on site-specific risk factors of recurrence regions in endometrial cancer patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620664/ https://www.ncbi.nlm.nih.gov/pubmed/36316771 http://dx.doi.org/10.1186/s12885-022-10193-3 |
work_keys_str_mv | AT shinwonkyo apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT yangseongj apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT parksangyoon apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT kangsokbom apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT leedongock apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT limmyongcheol apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT seosangsoo apredictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT shinwonkyo predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT yangseongj predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT parksangyoon predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT kangsokbom predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT leedongock predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT limmyongcheol predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients AT seosangsoo predictivemodelbasedonsitespecificriskfactorsofrecurrenceregionsinendometrialcancerpatients |