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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |