Cargando…

Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis

BACKGROUND: The five-year cumulative incidence rate in patients diagnosed with stage I small-cell lung cancer (SCLC) who were instructed to undergo surgery was from 40 to 60%.The death competition influence the accuracy of the classical survival analyses. The aim of the study is to investigate the m...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Jianjie, Zheng, Qiwen, Zhao, Xinghui, Zhao, Jun, An, Tongtong, Wu, Meina, Wang, Yuyan, Zhuo, Minglei, Zhong, Jia, Yang, Xue, Jia, Bo, Chen, Hanxiao, Dong, Zhi, Wang, Jingjing, Chi, Yujia, Zhai, Xiaoyu, Wang, Ziping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445928/
https://www.ncbi.nlm.nih.gov/pubmed/32838776
http://dx.doi.org/10.1186/s12885-020-07271-9
_version_ 1783574079748440064
author Li, Jianjie
Zheng, Qiwen
Zhao, Xinghui
Zhao, Jun
An, Tongtong
Wu, Meina
Wang, Yuyan
Zhuo, Minglei
Zhong, Jia
Yang, Xue
Jia, Bo
Chen, Hanxiao
Dong, Zhi
Wang, Jingjing
Chi, Yujia
Zhai, Xiaoyu
Wang, Ziping
author_facet Li, Jianjie
Zheng, Qiwen
Zhao, Xinghui
Zhao, Jun
An, Tongtong
Wu, Meina
Wang, Yuyan
Zhuo, Minglei
Zhong, Jia
Yang, Xue
Jia, Bo
Chen, Hanxiao
Dong, Zhi
Wang, Jingjing
Chi, Yujia
Zhai, Xiaoyu
Wang, Ziping
author_sort Li, Jianjie
collection PubMed
description BACKGROUND: The five-year cumulative incidence rate in patients diagnosed with stage I small-cell lung cancer (SCLC) who were instructed to undergo surgery was from 40 to 60%.The death competition influence the accuracy of the classical survival analyses. The aim of the study is to investigate the mortality of stage I small-cell lung cancer (SCLC) patients in the presence of competing risks according to a proportional hazards model, and to establish a competing risk nomogram to predict probabilities of both cause-specific death and death resulting from other causes. METHODS: The study subjects were patients diagnosed with stage I SCLC according to ICD-O-3. First, the cumulative incidence functions (CIFs) of cause-specific death, as well as of death resulting from other causes, were calculated. Then, a proportional hazards model for the sub-distribution of competing risks and a monogram were constructed to evaluate the probability of mortality in stage I SCLC patients. RESULTS: 1811 patients were included in this study. The five-year probabilities of death due to specific causes and other causes were 61.5 and 13.6%, respectively. Tumor size, extent of tumor, surgery, and radiotherapy were identified as the predictors of death resulting from specific causes in stage I SCLC. The results showed that surgery could effectively reduce the cancer-specific death, and the one-year cumulative incidence dropped from 34.5 to 11.2%. Like surgery, chemotherapy and radiotherapy improved the one-year survival rate. CONCLUSIONS: We constructed a predictive model for stage I SCLC using the data from the SEER database. The proportional sub-distribution models of competing risks revealed the predictors of death resulting from both specific causes and other causes. The competing risk nomogram that we built to predict the prognosis showed good reliability and could provide beneficial and individualized predictive information for stage I SCLC patients.
format Online
Article
Text
id pubmed-7445928
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-74459282020-08-26 Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis Li, Jianjie Zheng, Qiwen Zhao, Xinghui Zhao, Jun An, Tongtong Wu, Meina Wang, Yuyan Zhuo, Minglei Zhong, Jia Yang, Xue Jia, Bo Chen, Hanxiao Dong, Zhi Wang, Jingjing Chi, Yujia Zhai, Xiaoyu Wang, Ziping BMC Cancer Research Article BACKGROUND: The five-year cumulative incidence rate in patients diagnosed with stage I small-cell lung cancer (SCLC) who were instructed to undergo surgery was from 40 to 60%.The death competition influence the accuracy of the classical survival analyses. The aim of the study is to investigate the mortality of stage I small-cell lung cancer (SCLC) patients in the presence of competing risks according to a proportional hazards model, and to establish a competing risk nomogram to predict probabilities of both cause-specific death and death resulting from other causes. METHODS: The study subjects were patients diagnosed with stage I SCLC according to ICD-O-3. First, the cumulative incidence functions (CIFs) of cause-specific death, as well as of death resulting from other causes, were calculated. Then, a proportional hazards model for the sub-distribution of competing risks and a monogram were constructed to evaluate the probability of mortality in stage I SCLC patients. RESULTS: 1811 patients were included in this study. The five-year probabilities of death due to specific causes and other causes were 61.5 and 13.6%, respectively. Tumor size, extent of tumor, surgery, and radiotherapy were identified as the predictors of death resulting from specific causes in stage I SCLC. The results showed that surgery could effectively reduce the cancer-specific death, and the one-year cumulative incidence dropped from 34.5 to 11.2%. Like surgery, chemotherapy and radiotherapy improved the one-year survival rate. CONCLUSIONS: We constructed a predictive model for stage I SCLC using the data from the SEER database. The proportional sub-distribution models of competing risks revealed the predictors of death resulting from both specific causes and other causes. The competing risk nomogram that we built to predict the prognosis showed good reliability and could provide beneficial and individualized predictive information for stage I SCLC patients. BioMed Central 2020-08-24 /pmc/articles/PMC7445928/ /pubmed/32838776 http://dx.doi.org/10.1186/s12885-020-07271-9 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
Li, Jianjie
Zheng, Qiwen
Zhao, Xinghui
Zhao, Jun
An, Tongtong
Wu, Meina
Wang, Yuyan
Zhuo, Minglei
Zhong, Jia
Yang, Xue
Jia, Bo
Chen, Hanxiao
Dong, Zhi
Wang, Jingjing
Chi, Yujia
Zhai, Xiaoyu
Wang, Ziping
Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis
title Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis
title_full Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis
title_fullStr Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis
title_full_unstemmed Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis
title_short Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis
title_sort nomogram model for predicting cause-specific mortality in patients with stage i small-cell lung cancer: a competing risk analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445928/
https://www.ncbi.nlm.nih.gov/pubmed/32838776
http://dx.doi.org/10.1186/s12885-020-07271-9
work_keys_str_mv AT lijianjie nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT zhengqiwen nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT zhaoxinghui nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT zhaojun nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT antongtong nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT wumeina nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT wangyuyan nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT zhuominglei nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT zhongjia nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT yangxue nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT jiabo nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT chenhanxiao nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT dongzhi nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT wangjingjing nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT chiyujia nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT zhaixiaoyu nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis
AT wangziping nomogrammodelforpredictingcausespecificmortalityinpatientswithstageismallcelllungcanceracompetingriskanalysis