Cargando…

Establishment of age group classification for risk stratification in glioma patients

BACKGROUND: Age is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients. METHODS: 1502 p...

Descripción completa

Detalles Bibliográficos
Autores principales: Lin, Zhiying, Yang, Runwei, Li, Kaishu, Yi, Guozhong, Li, Zhiyong, Guo, Jinglin, Zhang, Zhou, Junxiang, Peng, Liu, Yawei, Qi, Songtao, Huang, Guanglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439690/
https://www.ncbi.nlm.nih.gov/pubmed/32819307
http://dx.doi.org/10.1186/s12883-020-01888-w
_version_ 1783573030833750016
author Lin, Zhiying
Yang, Runwei
Li, Kaishu
Yi, Guozhong
Li, Zhiyong
Guo, Jinglin
Zhang, Zhou
Junxiang, Peng
Liu, Yawei
Qi, Songtao
Huang, Guanglong
author_facet Lin, Zhiying
Yang, Runwei
Li, Kaishu
Yi, Guozhong
Li, Zhiyong
Guo, Jinglin
Zhang, Zhou
Junxiang, Peng
Liu, Yawei
Qi, Songtao
Huang, Guanglong
author_sort Lin, Zhiying
collection PubMed
description BACKGROUND: Age is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients. METHODS: 1502 patients diagnosed with gliomas at Nanfang Hospital between 2000 and 2018 were enrolled. The WHO grade of glioma was used as a dependent variable to evaluate the effect of age on risk stratification. The evaluation model was established by logistic regression, and the Akaike information criterion (AIC) value of the model was used to determine the optimal cutoff points for age-classification. The differences in gender, WHO grade, pathological subtype, tumor cell differentiation, tumor size, tumor location, and molecular markers between different age groups were analyzed. The molecular markers included GFAP, EMA, MGMT, P53, NeuN, Oligo2, EGFR, VEGF, IDH1, Ki-67, PR, CD3, H3K27M, TS, and 1p/19q status. RESULTS: The proportion of men with glioma was higher than that of women with glioma (58.3% vs 41.7%). Analysis of age showed that appropriate classifications of age group were 0–14 years old (pediatric group), 15–47 years old (youth group), 48–63 years old (middle-aged group), and ≥ 64 years old (elderly group).The proportions of glioblastoma and large tumor size (4–6 cm) increased with age (p = 0.000, p = 0.018, respectively). Analysis of the pathological molecular markers across the four age groups showed that the proportion of patients with larger than 10% area of Ki-67 expression or positive PR expression increased with age (p = 0.000, p = 0.017, respectively). CONCLUSIONS: Appropriate classifications of the age group for risk stratification are 0–14 years old (pediatric group), 15–47 years old (young group), 48–63 years old (middle age group) and ≥ 64 years old (elderly group). This age group classification is effective in evaluating the risk of glioblastoma in glioma patients.
format Online
Article
Text
id pubmed-7439690
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-74396902020-08-24 Establishment of age group classification for risk stratification in glioma patients Lin, Zhiying Yang, Runwei Li, Kaishu Yi, Guozhong Li, Zhiyong Guo, Jinglin Zhang, Zhou Junxiang, Peng Liu, Yawei Qi, Songtao Huang, Guanglong BMC Neurol Research Article BACKGROUND: Age is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients. METHODS: 1502 patients diagnosed with gliomas at Nanfang Hospital between 2000 and 2018 were enrolled. The WHO grade of glioma was used as a dependent variable to evaluate the effect of age on risk stratification. The evaluation model was established by logistic regression, and the Akaike information criterion (AIC) value of the model was used to determine the optimal cutoff points for age-classification. The differences in gender, WHO grade, pathological subtype, tumor cell differentiation, tumor size, tumor location, and molecular markers between different age groups were analyzed. The molecular markers included GFAP, EMA, MGMT, P53, NeuN, Oligo2, EGFR, VEGF, IDH1, Ki-67, PR, CD3, H3K27M, TS, and 1p/19q status. RESULTS: The proportion of men with glioma was higher than that of women with glioma (58.3% vs 41.7%). Analysis of age showed that appropriate classifications of age group were 0–14 years old (pediatric group), 15–47 years old (youth group), 48–63 years old (middle-aged group), and ≥ 64 years old (elderly group).The proportions of glioblastoma and large tumor size (4–6 cm) increased with age (p = 0.000, p = 0.018, respectively). Analysis of the pathological molecular markers across the four age groups showed that the proportion of patients with larger than 10% area of Ki-67 expression or positive PR expression increased with age (p = 0.000, p = 0.017, respectively). CONCLUSIONS: Appropriate classifications of the age group for risk stratification are 0–14 years old (pediatric group), 15–47 years old (young group), 48–63 years old (middle age group) and ≥ 64 years old (elderly group). This age group classification is effective in evaluating the risk of glioblastoma in glioma patients. BioMed Central 2020-08-20 /pmc/articles/PMC7439690/ /pubmed/32819307 http://dx.doi.org/10.1186/s12883-020-01888-w Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 Article
Lin, Zhiying
Yang, Runwei
Li, Kaishu
Yi, Guozhong
Li, Zhiyong
Guo, Jinglin
Zhang, Zhou
Junxiang, Peng
Liu, Yawei
Qi, Songtao
Huang, Guanglong
Establishment of age group classification for risk stratification in glioma patients
title Establishment of age group classification for risk stratification in glioma patients
title_full Establishment of age group classification for risk stratification in glioma patients
title_fullStr Establishment of age group classification for risk stratification in glioma patients
title_full_unstemmed Establishment of age group classification for risk stratification in glioma patients
title_short Establishment of age group classification for risk stratification in glioma patients
title_sort establishment of age group classification for risk stratification in glioma patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439690/
https://www.ncbi.nlm.nih.gov/pubmed/32819307
http://dx.doi.org/10.1186/s12883-020-01888-w
work_keys_str_mv AT linzhiying establishmentofagegroupclassificationforriskstratificationingliomapatients
AT yangrunwei establishmentofagegroupclassificationforriskstratificationingliomapatients
AT likaishu establishmentofagegroupclassificationforriskstratificationingliomapatients
AT yiguozhong establishmentofagegroupclassificationforriskstratificationingliomapatients
AT lizhiyong establishmentofagegroupclassificationforriskstratificationingliomapatients
AT guojinglin establishmentofagegroupclassificationforriskstratificationingliomapatients
AT zhangzhou establishmentofagegroupclassificationforriskstratificationingliomapatients
AT junxiangpeng establishmentofagegroupclassificationforriskstratificationingliomapatients
AT liuyawei establishmentofagegroupclassificationforriskstratificationingliomapatients
AT qisongtao establishmentofagegroupclassificationforriskstratificationingliomapatients
AT huangguanglong establishmentofagegroupclassificationforriskstratificationingliomapatients