Cargando…
Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database
BACKGROUND: Hemangioblastomas are uncommon, benign neoplasms of the central nervous system (CNS). This study aims to evaluate the incidence, demographics, clinical characteristics, and prognosis of CNS hemangioblastomas using the data from the Surveillance, Epidemiology, and End Results (SEER) Progr...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509109/ https://www.ncbi.nlm.nih.gov/pubmed/33014882 http://dx.doi.org/10.3389/fonc.2020.570103 |
_version_ | 1783585536371326976 |
---|---|
author | Yin, Xiangdong Duan, Hongzhou Yi, Zhiqiang Li, Chunwei Lu, Runchun Li, Liang |
author_facet | Yin, Xiangdong Duan, Hongzhou Yi, Zhiqiang Li, Chunwei Lu, Runchun Li, Liang |
author_sort | Yin, Xiangdong |
collection | PubMed |
description | BACKGROUND: Hemangioblastomas are uncommon, benign neoplasms of the central nervous system (CNS). This study aims to evaluate the incidence, demographics, clinical characteristics, and prognosis of CNS hemangioblastomas using the data from the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Univariate and multivariate analyses using the Cox proportional hazards model were employed to identify prognostic factors of overall survival. The Kaplan-Meier method was utilized to evaluate overall survival distribution by treatment modality. A nomogram was further built to predict survival at 3 and 5 years. RESULTS: The overall incidence rate of CNS hemangioblastomas was 0.141 per 100,000 person-years. Through univariate analysis and multivariate analyses, age between 60 and 79 years (HR = 3.697, p < 0.001), age greater than 80 years (HR = 12.318, p < 0.001), African American race (HR = 1.857, p = 0.003), multiple tumors (HR = 1.715, p < 0.001), and prior surgery (HR = 0.638, p = 0.013) were significantly associated with overall survival. Patients receiving surgery alone had better overall survival compared with patients receiving no treatment (p = 0.008) and patients receiving both surgery and radiotherapy (p = 0.002). The calibration plots demonstrated an excellent agreement between nomogram-predicted and actual survival. CONCLUSION: In conclusion, age, race, tumor location, number of tumors, and prior surgery are prognostic factors for survival. Surgery was the most common modality and was suggested as an effective and optimal treatment. The proposed nomogram can predict the prognosis of patients with CNS hemangioblastomas and help clinicians in making decisions. |
format | Online Article Text |
id | pubmed-7509109 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75091092020-10-02 Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database Yin, Xiangdong Duan, Hongzhou Yi, Zhiqiang Li, Chunwei Lu, Runchun Li, Liang Front Oncol Oncology BACKGROUND: Hemangioblastomas are uncommon, benign neoplasms of the central nervous system (CNS). This study aims to evaluate the incidence, demographics, clinical characteristics, and prognosis of CNS hemangioblastomas using the data from the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Univariate and multivariate analyses using the Cox proportional hazards model were employed to identify prognostic factors of overall survival. The Kaplan-Meier method was utilized to evaluate overall survival distribution by treatment modality. A nomogram was further built to predict survival at 3 and 5 years. RESULTS: The overall incidence rate of CNS hemangioblastomas was 0.141 per 100,000 person-years. Through univariate analysis and multivariate analyses, age between 60 and 79 years (HR = 3.697, p < 0.001), age greater than 80 years (HR = 12.318, p < 0.001), African American race (HR = 1.857, p = 0.003), multiple tumors (HR = 1.715, p < 0.001), and prior surgery (HR = 0.638, p = 0.013) were significantly associated with overall survival. Patients receiving surgery alone had better overall survival compared with patients receiving no treatment (p = 0.008) and patients receiving both surgery and radiotherapy (p = 0.002). The calibration plots demonstrated an excellent agreement between nomogram-predicted and actual survival. CONCLUSION: In conclusion, age, race, tumor location, number of tumors, and prior surgery are prognostic factors for survival. Surgery was the most common modality and was suggested as an effective and optimal treatment. The proposed nomogram can predict the prognosis of patients with CNS hemangioblastomas and help clinicians in making decisions. Frontiers Media S.A. 2020-09-09 /pmc/articles/PMC7509109/ /pubmed/33014882 http://dx.doi.org/10.3389/fonc.2020.570103 Text en Copyright © 2020 Yin, Duan, Yi, Li, Lu and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yin, Xiangdong Duan, Hongzhou Yi, Zhiqiang Li, Chunwei Lu, Runchun Li, Liang Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database |
title | Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database |
title_full | Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database |
title_fullStr | Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database |
title_full_unstemmed | Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database |
title_short | Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database |
title_sort | incidence, prognostic factors and survival for hemangioblastoma of the central nervous system: analysis based on the surveillance, epidemiology, and end results database |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509109/ https://www.ncbi.nlm.nih.gov/pubmed/33014882 http://dx.doi.org/10.3389/fonc.2020.570103 |
work_keys_str_mv | AT yinxiangdong incidenceprognosticfactorsandsurvivalforhemangioblastomaofthecentralnervoussystemanalysisbasedonthesurveillanceepidemiologyandendresultsdatabase AT duanhongzhou incidenceprognosticfactorsandsurvivalforhemangioblastomaofthecentralnervoussystemanalysisbasedonthesurveillanceepidemiologyandendresultsdatabase AT yizhiqiang incidenceprognosticfactorsandsurvivalforhemangioblastomaofthecentralnervoussystemanalysisbasedonthesurveillanceepidemiologyandendresultsdatabase AT lichunwei incidenceprognosticfactorsandsurvivalforhemangioblastomaofthecentralnervoussystemanalysisbasedonthesurveillanceepidemiologyandendresultsdatabase AT lurunchun incidenceprognosticfactorsandsurvivalforhemangioblastomaofthecentralnervoussystemanalysisbasedonthesurveillanceepidemiologyandendresultsdatabase AT liliang incidenceprognosticfactorsandsurvivalforhemangioblastomaofthecentralnervoussystemanalysisbasedonthesurveillanceepidemiologyandendresultsdatabase |