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Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters

BACKGROUND: Adjuvant therapy increases disease-free survival in endometrial cancer (EC), but has no impact on overall survival and negatively influences the quality of life. We investigated the discriminatory power of classical and immunological predictors of recurrence in a cohort of EC patients an...

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Autores principales: Versluis, M A, de Jong, R A, Plat, A, Bosse, T, Smit, V T, Mackay, H, Powell, M, Leary, A, Mileshkin, L, Kitchener, H C, Crosbie, E J, Edmondson, R J, Creutzberg, C L, Hollema, H, Daemen, T, de Bock, G H, Nijman, H W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4559831/
https://www.ncbi.nlm.nih.gov/pubmed/26217922
http://dx.doi.org/10.1038/bjc.2015.268
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author Versluis, M A
de Jong, R A
Plat, A
Bosse, T
Smit, V T
Mackay, H
Powell, M
Leary, A
Mileshkin, L
Kitchener, H C
Crosbie, E J
Edmondson, R J
Creutzberg, C L
Hollema, H
Daemen, T
de Bock, G H
Nijman, H W
author_facet Versluis, M A
de Jong, R A
Plat, A
Bosse, T
Smit, V T
Mackay, H
Powell, M
Leary, A
Mileshkin, L
Kitchener, H C
Crosbie, E J
Edmondson, R J
Creutzberg, C L
Hollema, H
Daemen, T
de Bock, G H
Nijman, H W
author_sort Versluis, M A
collection PubMed
description BACKGROUND: Adjuvant therapy increases disease-free survival in endometrial cancer (EC), but has no impact on overall survival and negatively influences the quality of life. We investigated the discriminatory power of classical and immunological predictors of recurrence in a cohort of EC patients and confirmed the findings in an independent validation cohort. METHODS: We reanalysed the data from 355 EC patients and tested our findings in an independent validation cohort of 72 patients with EC. Predictors were selected and Harrell's C-index for concordance was used to determine discriminatory power for disease-free survival in the total group and stratified for histological subtype. RESULTS: Predictors for recurrence were FIGO stage, lymphovascular space invasion and numbers of cytotoxic and memory T-cells. For high risk cancer, cytotoxic or memory T-cells predicted recurrence as well as a combination of FIGO stage and lymphovascular space invasion (C-index 0.67 and 0.71 vs 0.70). Recurrence was best predicted when FIGO stage, lymphovascular space invasion and numbers of cytotoxic cells were used in combination (C-index 0.82). Findings were confirmed in the validation cohort. CONCLUSIONS: In high-risk EC, clinicopathological or immunological variables can predict regional or distant recurrence with equal accuracy, but the use of these variables in combination is more powerful.
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spelling pubmed-45598312016-09-01 Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters Versluis, M A de Jong, R A Plat, A Bosse, T Smit, V T Mackay, H Powell, M Leary, A Mileshkin, L Kitchener, H C Crosbie, E J Edmondson, R J Creutzberg, C L Hollema, H Daemen, T de Bock, G H Nijman, H W Br J Cancer Molecular Diagnostics BACKGROUND: Adjuvant therapy increases disease-free survival in endometrial cancer (EC), but has no impact on overall survival and negatively influences the quality of life. We investigated the discriminatory power of classical and immunological predictors of recurrence in a cohort of EC patients and confirmed the findings in an independent validation cohort. METHODS: We reanalysed the data from 355 EC patients and tested our findings in an independent validation cohort of 72 patients with EC. Predictors were selected and Harrell's C-index for concordance was used to determine discriminatory power for disease-free survival in the total group and stratified for histological subtype. RESULTS: Predictors for recurrence were FIGO stage, lymphovascular space invasion and numbers of cytotoxic and memory T-cells. For high risk cancer, cytotoxic or memory T-cells predicted recurrence as well as a combination of FIGO stage and lymphovascular space invasion (C-index 0.67 and 0.71 vs 0.70). Recurrence was best predicted when FIGO stage, lymphovascular space invasion and numbers of cytotoxic cells were used in combination (C-index 0.82). Findings were confirmed in the validation cohort. CONCLUSIONS: In high-risk EC, clinicopathological or immunological variables can predict regional or distant recurrence with equal accuracy, but the use of these variables in combination is more powerful. Nature Publishing Group 2015-09-01 2015-07-28 /pmc/articles/PMC4559831/ /pubmed/26217922 http://dx.doi.org/10.1038/bjc.2015.268 Text en Copyright © 2015 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Molecular Diagnostics
Versluis, M A
de Jong, R A
Plat, A
Bosse, T
Smit, V T
Mackay, H
Powell, M
Leary, A
Mileshkin, L
Kitchener, H C
Crosbie, E J
Edmondson, R J
Creutzberg, C L
Hollema, H
Daemen, T
de Bock, G H
Nijman, H W
Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
title Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
title_full Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
title_fullStr Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
title_full_unstemmed Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
title_short Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
title_sort prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters
topic Molecular Diagnostics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4559831/
https://www.ncbi.nlm.nih.gov/pubmed/26217922
http://dx.doi.org/10.1038/bjc.2015.268
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