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The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates

OBJECTIVE: To examine the direct and indirect impact of comorbidity on the survival. DESIGN: A historical cohort study. SETTING: Denmark. PARTICIPANTS: All patients with non-small cell lung cancer who were registered in the Danish Lung Cancer Registry in 2010. MAIN OUTCOME MEASURES: The influence of...

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Autores principales: Iachina, Maria, Green, Anders, Jakobsen, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927932/
https://www.ncbi.nlm.nih.gov/pubmed/24523421
http://dx.doi.org/10.1136/bmjopen-2013-003846
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author Iachina, Maria
Green, Anders
Jakobsen, Erik
author_facet Iachina, Maria
Green, Anders
Jakobsen, Erik
author_sort Iachina, Maria
collection PubMed
description OBJECTIVE: To examine the direct and indirect impact of comorbidity on the survival. DESIGN: A historical cohort study. SETTING: Denmark. PARTICIPANTS: All patients with non-small cell lung cancer who were registered in the Danish Lung Cancer Registry in 2010. MAIN OUTCOME MEASURES: The influence of comorbidity on stage misclassification, probability of resection and survival. RESULTS: It was estimated that the comorbidity influences the probability of resection with OR 0.65 and 95% credible interval (0.54; 0.79), the staging process with OR 1.08 and 95% credible interval (0.96; 1.20), and the survival process with HR 1.08 and 95% credible interval (1.02; 1.14). CONCLUSIONS: We found that comorbidity has a significant indirect effect on survival mediated by the resection process and a slightly direct effect on mortality.
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spelling pubmed-39279322014-02-19 The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates Iachina, Maria Green, Anders Jakobsen, Erik BMJ Open Research Methods OBJECTIVE: To examine the direct and indirect impact of comorbidity on the survival. DESIGN: A historical cohort study. SETTING: Denmark. PARTICIPANTS: All patients with non-small cell lung cancer who were registered in the Danish Lung Cancer Registry in 2010. MAIN OUTCOME MEASURES: The influence of comorbidity on stage misclassification, probability of resection and survival. RESULTS: It was estimated that the comorbidity influences the probability of resection with OR 0.65 and 95% credible interval (0.54; 0.79), the staging process with OR 1.08 and 95% credible interval (0.96; 1.20), and the survival process with HR 1.08 and 95% credible interval (1.02; 1.14). CONCLUSIONS: We found that comorbidity has a significant indirect effect on survival mediated by the resection process and a slightly direct effect on mortality. BMJ Publishing Group 2014-02-12 /pmc/articles/PMC3927932/ /pubmed/24523421 http://dx.doi.org/10.1136/bmjopen-2013-003846 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Research Methods
Iachina, Maria
Green, Anders
Jakobsen, Erik
The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
title The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
title_full The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
title_fullStr The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
title_full_unstemmed The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
title_short The direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
title_sort direct and indirect impact of comorbidity on the survival of patients with non-small cell lung cancer: a combination of survival, staging and resection models with missing measurements in covariates
topic Research Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927932/
https://www.ncbi.nlm.nih.gov/pubmed/24523421
http://dx.doi.org/10.1136/bmjopen-2013-003846
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