Cargando…

Status and prognostic nomogram of patients with Burkitt lymphoma

The purpose of the present study was to evaluate the newest status of patients diagnosed Burkitt lymphoma (BL), an aggressive lymphoma subset with a high cure rate. Furthermore, the study aimed to create prognostic nomograms to consider various prognostic factors and estimate patient survival, pavin...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Jielun, Tan, Huo, Li, Bo, Chen, Shuyi, Xu, Lihua, Zou, Yawei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924199/
https://www.ncbi.nlm.nih.gov/pubmed/31897210
http://dx.doi.org/10.3892/ol.2019.11155
_version_ 1783481681722736640
author Lu, Jielun
Tan, Huo
Li, Bo
Chen, Shuyi
Xu, Lihua
Zou, Yawei
author_facet Lu, Jielun
Tan, Huo
Li, Bo
Chen, Shuyi
Xu, Lihua
Zou, Yawei
author_sort Lu, Jielun
collection PubMed
description The purpose of the present study was to evaluate the newest status of patients diagnosed Burkitt lymphoma (BL), an aggressive lymphoma subset with a high cure rate. Furthermore, the study aimed to create prognostic nomograms to consider various prognostic factors and estimate patient survival, paving the way for clinical decision-making. A total of 4,600 patients diagnosed with BL between 1983 and 2015 were investigated, via data collected from the SEER database. The overall status of the patients was analyzed through several aspects, including incidence and survival analysis of the previous three decades using the log-rank test and the Kaplan-Meier method. In order to construct and validate the nomograms, the patient diagnosed during 2005–2015 were randomly assigned to the training cohort and validation cohort. Univariate and multivariate analyses were applied to identify independent factors that were further included in the nomograms, predicting 3- and 5-year overall survival (OS) and cancer-specific survival (CSS). The data of the training cohort were used for internal validation and validation cohort used to external validation. C-index and calibration plots were used to validate the nomograms, comparing predicted values with actual outcomes. The incidence of BL was gradually increased from 1984 and reached its peak in 2009, at a rate of 0.491 per 100,000 [95% confidence interval (CI), 0.412–0.581]. From 2009, the incidence slowly declined year by year and dropped to 0.280 per 100,000 (95% CI, 0.224–0.346). The OS and CSS rates of patients diagnosed between 2005 and 2015 were increased, in contrast with those of patients diagnosed from 1983–1993 and 1994–2004. A total of five variables, including age, race, chemotherapy, primary site and stage, proved to be the prognostic factors of BL and were used to construct the nomograms predicting 3- and 5-year OS and CSS. The internal and external calibration plots for the probability of 3- and 5-year OS and CSS were consistent between nomogram prediction and observed outcomes. The slow decline in incidence and the significantly improved cure rate make BL a disease that is no longer an urgent problem. Effective nomograms were developed to predict the OS and CSS of patients with BL.
format Online
Article
Text
id pubmed-6924199
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher D.A. Spandidos
record_format MEDLINE/PubMed
spelling pubmed-69241992020-01-02 Status and prognostic nomogram of patients with Burkitt lymphoma Lu, Jielun Tan, Huo Li, Bo Chen, Shuyi Xu, Lihua Zou, Yawei Oncol Lett Articles The purpose of the present study was to evaluate the newest status of patients diagnosed Burkitt lymphoma (BL), an aggressive lymphoma subset with a high cure rate. Furthermore, the study aimed to create prognostic nomograms to consider various prognostic factors and estimate patient survival, paving the way for clinical decision-making. A total of 4,600 patients diagnosed with BL between 1983 and 2015 were investigated, via data collected from the SEER database. The overall status of the patients was analyzed through several aspects, including incidence and survival analysis of the previous three decades using the log-rank test and the Kaplan-Meier method. In order to construct and validate the nomograms, the patient diagnosed during 2005–2015 were randomly assigned to the training cohort and validation cohort. Univariate and multivariate analyses were applied to identify independent factors that were further included in the nomograms, predicting 3- and 5-year overall survival (OS) and cancer-specific survival (CSS). The data of the training cohort were used for internal validation and validation cohort used to external validation. C-index and calibration plots were used to validate the nomograms, comparing predicted values with actual outcomes. The incidence of BL was gradually increased from 1984 and reached its peak in 2009, at a rate of 0.491 per 100,000 [95% confidence interval (CI), 0.412–0.581]. From 2009, the incidence slowly declined year by year and dropped to 0.280 per 100,000 (95% CI, 0.224–0.346). The OS and CSS rates of patients diagnosed between 2005 and 2015 were increased, in contrast with those of patients diagnosed from 1983–1993 and 1994–2004. A total of five variables, including age, race, chemotherapy, primary site and stage, proved to be the prognostic factors of BL and were used to construct the nomograms predicting 3- and 5-year OS and CSS. The internal and external calibration plots for the probability of 3- and 5-year OS and CSS were consistent between nomogram prediction and observed outcomes. The slow decline in incidence and the significantly improved cure rate make BL a disease that is no longer an urgent problem. Effective nomograms were developed to predict the OS and CSS of patients with BL. D.A. Spandidos 2020-01 2019-11-28 /pmc/articles/PMC6924199/ /pubmed/31897210 http://dx.doi.org/10.3892/ol.2019.11155 Text en Copyright: © Lu et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Lu, Jielun
Tan, Huo
Li, Bo
Chen, Shuyi
Xu, Lihua
Zou, Yawei
Status and prognostic nomogram of patients with Burkitt lymphoma
title Status and prognostic nomogram of patients with Burkitt lymphoma
title_full Status and prognostic nomogram of patients with Burkitt lymphoma
title_fullStr Status and prognostic nomogram of patients with Burkitt lymphoma
title_full_unstemmed Status and prognostic nomogram of patients with Burkitt lymphoma
title_short Status and prognostic nomogram of patients with Burkitt lymphoma
title_sort status and prognostic nomogram of patients with burkitt lymphoma
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924199/
https://www.ncbi.nlm.nih.gov/pubmed/31897210
http://dx.doi.org/10.3892/ol.2019.11155
work_keys_str_mv AT lujielun statusandprognosticnomogramofpatientswithburkittlymphoma
AT tanhuo statusandprognosticnomogramofpatientswithburkittlymphoma
AT libo statusandprognosticnomogramofpatientswithburkittlymphoma
AT chenshuyi statusandprognosticnomogramofpatientswithburkittlymphoma
AT xulihua statusandprognosticnomogramofpatientswithburkittlymphoma
AT zouyawei statusandprognosticnomogramofpatientswithburkittlymphoma