Cargando…
A novel model to estimate lymph node metastasis in endometrial cancer patients
OBJECTIVES: To evaluate the postoperative pathological characteristics of hysterectomy specimens, preoperative cancer antigen (CA)-125 levels and imaging modalities in patients with endometrial cancer and to build a risk matrix model to identify and recruit patients for retroperitoneal lymphadenecto...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5251192/ https://www.ncbi.nlm.nih.gov/pubmed/28226030 http://dx.doi.org/10.6061/clinics/2017(01)06 |
_version_ | 1782497765635391488 |
---|---|
author | Anton, Cristina e Silva, Alexandre Silva Baracat, Edmund Chada Dogan, Nasuh Utku Köhler, Christhardt Carvalho, Jesus Paula di Favero, Giovanni Mastrantonio |
author_facet | Anton, Cristina e Silva, Alexandre Silva Baracat, Edmund Chada Dogan, Nasuh Utku Köhler, Christhardt Carvalho, Jesus Paula di Favero, Giovanni Mastrantonio |
author_sort | Anton, Cristina |
collection | PubMed |
description | OBJECTIVES: To evaluate the postoperative pathological characteristics of hysterectomy specimens, preoperative cancer antigen (CA)-125 levels and imaging modalities in patients with endometrial cancer and to build a risk matrix model to identify and recruit patients for retroperitoneal lymphadenectomy. METHODS: A total of 405 patients undergoing surgical treatment for endometrial cancer were retrospectively reviewed and analyzed. Clinical (age and body mass index), laboratory (CA-125), radiological (lymph node evaluation), and pathological (tumour size, grade, lymphovascular space invasion, lymph node metastasis, and myometrial invasion) parameters were used to test the ability to predict lymph node metastasis. Four parameters were selected by logistic regression to create a risk matrix for nodal metastasis. RESULTS: Of the 405 patients, 236 (58.3%) underwent complete pelvic and para-aortic lymphadenectomy, 96 (23.7%) underwent nodal sampling, and 73 (18%) had no surgical lymph node assessment. The parameters predicting nodal involvement obtained through logistic regression were myometrial infiltration >50%, lymphovascular space involvement, pelvic lymph node involvement by imaging, and a CA-125 value >21.5 U/mL. According to our risk matrix, the absence of these four parameters implied a risk of lymph node metastasis of 2.7%, whereas in the presence of all four parameters the risk was 82.3%. CONCLUSION: Patients without deep myometrial invasion and lymphovascular space involvement on the final pathological examination and with normal CA-125 values and lymph node radiological examinations have a relatively low risk of lymph node involvement. This risk assessment matrix may be able to refer patients with high-risk parameters necessitating lymphadenectomy and to decide the risks and benefits of lymphadenectomy. |
format | Online Article Text |
id | pubmed-5251192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo |
record_format | MEDLINE/PubMed |
spelling | pubmed-52511922017-01-25 A novel model to estimate lymph node metastasis in endometrial cancer patients Anton, Cristina e Silva, Alexandre Silva Baracat, Edmund Chada Dogan, Nasuh Utku Köhler, Christhardt Carvalho, Jesus Paula di Favero, Giovanni Mastrantonio Clinics (Sao Paulo) Clinical Science OBJECTIVES: To evaluate the postoperative pathological characteristics of hysterectomy specimens, preoperative cancer antigen (CA)-125 levels and imaging modalities in patients with endometrial cancer and to build a risk matrix model to identify and recruit patients for retroperitoneal lymphadenectomy. METHODS: A total of 405 patients undergoing surgical treatment for endometrial cancer were retrospectively reviewed and analyzed. Clinical (age and body mass index), laboratory (CA-125), radiological (lymph node evaluation), and pathological (tumour size, grade, lymphovascular space invasion, lymph node metastasis, and myometrial invasion) parameters were used to test the ability to predict lymph node metastasis. Four parameters were selected by logistic regression to create a risk matrix for nodal metastasis. RESULTS: Of the 405 patients, 236 (58.3%) underwent complete pelvic and para-aortic lymphadenectomy, 96 (23.7%) underwent nodal sampling, and 73 (18%) had no surgical lymph node assessment. The parameters predicting nodal involvement obtained through logistic regression were myometrial infiltration >50%, lymphovascular space involvement, pelvic lymph node involvement by imaging, and a CA-125 value >21.5 U/mL. According to our risk matrix, the absence of these four parameters implied a risk of lymph node metastasis of 2.7%, whereas in the presence of all four parameters the risk was 82.3%. CONCLUSION: Patients without deep myometrial invasion and lymphovascular space involvement on the final pathological examination and with normal CA-125 values and lymph node radiological examinations have a relatively low risk of lymph node involvement. This risk assessment matrix may be able to refer patients with high-risk parameters necessitating lymphadenectomy and to decide the risks and benefits of lymphadenectomy. Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo 2017-01 2017-01 /pmc/articles/PMC5251192/ /pubmed/28226030 http://dx.doi.org/10.6061/clinics/2017(01)06 Text en Copyright © 2017 CLINICS http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is properly cited. |
spellingShingle | Clinical Science Anton, Cristina e Silva, Alexandre Silva Baracat, Edmund Chada Dogan, Nasuh Utku Köhler, Christhardt Carvalho, Jesus Paula di Favero, Giovanni Mastrantonio A novel model to estimate lymph node metastasis in endometrial cancer patients |
title | A novel model to estimate lymph node metastasis in endometrial cancer patients |
title_full | A novel model to estimate lymph node metastasis in endometrial cancer patients |
title_fullStr | A novel model to estimate lymph node metastasis in endometrial cancer patients |
title_full_unstemmed | A novel model to estimate lymph node metastasis in endometrial cancer patients |
title_short | A novel model to estimate lymph node metastasis in endometrial cancer patients |
title_sort | novel model to estimate lymph node metastasis in endometrial cancer patients |
topic | Clinical Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5251192/ https://www.ncbi.nlm.nih.gov/pubmed/28226030 http://dx.doi.org/10.6061/clinics/2017(01)06 |
work_keys_str_mv | AT antoncristina anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT esilvaalexandresilva anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT baracatedmundchada anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT dogannasuhutku anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT kohlerchristhardt anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT carvalhojesuspaula anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT difaverogiovannimastrantonio anovelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT antoncristina novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT esilvaalexandresilva novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT baracatedmundchada novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT dogannasuhutku novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT kohlerchristhardt novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT carvalhojesuspaula novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients AT difaverogiovannimastrantonio novelmodeltoestimatelymphnodemetastasisinendometrialcancerpatients |