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Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?

OBJECTIVE: Elderly age is one of the poor prognostic factors in epithelial ovarian cancer (EOC), but the optimal age cut-off is not known. The present study sought to identify the ideal age cutoff that represents a negative prognostic factor in EOC, considering the geriatric assessment. METHODS: Haz...

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Autores principales: Kim, Jihye, Chang, Youjean, Kim, Tae-Joong, Lee, Jeong-Won, Kim, Byoung-Gie, Bae, Duk-Soo, Choi, Chel Hun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6304408/
https://www.ncbi.nlm.nih.gov/pubmed/30479095
http://dx.doi.org/10.3802/jgo.2019.30.e11
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author Kim, Jihye
Chang, Youjean
Kim, Tae-Joong
Lee, Jeong-Won
Kim, Byoung-Gie
Bae, Duk-Soo
Choi, Chel Hun
author_facet Kim, Jihye
Chang, Youjean
Kim, Tae-Joong
Lee, Jeong-Won
Kim, Byoung-Gie
Bae, Duk-Soo
Choi, Chel Hun
author_sort Kim, Jihye
collection PubMed
description OBJECTIVE: Elderly age is one of the poor prognostic factors in epithelial ovarian cancer (EOC), but the optimal age cut-off is not known. The present study sought to identify the ideal age cutoff that represents a negative prognostic factor in EOC, considering the geriatric assessment. METHODS: Hazard ratios (HRs) with p-values were calculated using all possible age cutoffs with stage, histology, grade, optimality and comorbidities as covariates in multivariate Cox regression model. The trends of p-value and HR by age cutoff were further evaluated in a subgroup of histology and in The Cancer Genome Atlas (TCGA) dataset. In addition, propensity score-matching analysis using the identified age cutoff was performed. RESULTS: An age of 66 years was shown to be the most significant cutoff for defining old age with independent prognostic power (HR=1.45; 95% confidence interval=1.04–2.03; p=0.027). This result was also observed with the analyses of serous histology subgroup and with the analysis of a TCGA dataset with serous EOC. In survival analysis, patients aged ≥66 years had significantly worse overall survival compared with younger individuals (56 months vs. 87 months; p=0.006), even following propensity score matching (57 vs. 78 months; p=0.038). CONCLUSION: An age of 66 years is the best cutoff to define elderly age in serous EOC patients considering the geriatric assessment, and this information can be used in the administration of individualized therapies in elderly EOC patients.
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spelling pubmed-63044082019-01-01 Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff? Kim, Jihye Chang, Youjean Kim, Tae-Joong Lee, Jeong-Won Kim, Byoung-Gie Bae, Duk-Soo Choi, Chel Hun J Gynecol Oncol Original Article OBJECTIVE: Elderly age is one of the poor prognostic factors in epithelial ovarian cancer (EOC), but the optimal age cut-off is not known. The present study sought to identify the ideal age cutoff that represents a negative prognostic factor in EOC, considering the geriatric assessment. METHODS: Hazard ratios (HRs) with p-values were calculated using all possible age cutoffs with stage, histology, grade, optimality and comorbidities as covariates in multivariate Cox regression model. The trends of p-value and HR by age cutoff were further evaluated in a subgroup of histology and in The Cancer Genome Atlas (TCGA) dataset. In addition, propensity score-matching analysis using the identified age cutoff was performed. RESULTS: An age of 66 years was shown to be the most significant cutoff for defining old age with independent prognostic power (HR=1.45; 95% confidence interval=1.04–2.03; p=0.027). This result was also observed with the analyses of serous histology subgroup and with the analysis of a TCGA dataset with serous EOC. In survival analysis, patients aged ≥66 years had significantly worse overall survival compared with younger individuals (56 months vs. 87 months; p=0.006), even following propensity score matching (57 vs. 78 months; p=0.038). CONCLUSION: An age of 66 years is the best cutoff to define elderly age in serous EOC patients considering the geriatric assessment, and this information can be used in the administration of individualized therapies in elderly EOC patients. Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology 2018-10-22 /pmc/articles/PMC6304408/ /pubmed/30479095 http://dx.doi.org/10.3802/jgo.2019.30.e11 Text en Copyright © 2019. Asian Society of Gynecologic Oncology, Korean Society of Gynecologic Oncology https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Kim, Jihye
Chang, Youjean
Kim, Tae-Joong
Lee, Jeong-Won
Kim, Byoung-Gie
Bae, Duk-Soo
Choi, Chel Hun
Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
title Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
title_full Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
title_fullStr Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
title_full_unstemmed Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
title_short Optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
title_sort optimal cutoff age for predicting prognosis associated with serous epithelial ovarian cancer: what is the best age cutoff?
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6304408/
https://www.ncbi.nlm.nih.gov/pubmed/30479095
http://dx.doi.org/10.3802/jgo.2019.30.e11
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