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Competing Risk Analyses of Patients with End-Stage Renal Disease

INTRODUCTION: Chronic kidney disease (CKD) is an important health problem that gradually leads to end-stage renal disease (ESRD). In ESRD patients, death due to other diseases or some events, such as renal transplantation (known as competing risks), would change the probability of observing the even...

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Autores principales: Tabrizi, Reza, Moosazadeh, Mahmood, Sekhavati, Eghbal, Jalali, Maryam, Afshari, Mahdi, Akbari, Maryam, Baneshi, Mohammad Reza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Electronic physician 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4700890/
https://www.ncbi.nlm.nih.gov/pubmed/26767098
http://dx.doi.org/10.19082/1458
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author Tabrizi, Reza
Moosazadeh, Mahmood
Sekhavati, Eghbal
Jalali, Maryam
Afshari, Mahdi
Akbari, Maryam
Baneshi, Mohammad Reza
author_facet Tabrizi, Reza
Moosazadeh, Mahmood
Sekhavati, Eghbal
Jalali, Maryam
Afshari, Mahdi
Akbari, Maryam
Baneshi, Mohammad Reza
author_sort Tabrizi, Reza
collection PubMed
description INTRODUCTION: Chronic kidney disease (CKD) is an important health problem that gradually leads to end-stage renal disease (ESRD). In ESRD patients, death due to other diseases or some events, such as renal transplantation (known as competing risks), would change the probability of observing the event of interest. The aim of this study was to estimate the survival of ESRD patients using competing risk analyses. METHODS: In this retrospective longitudinal study, 307 ESRD patients who were older than 20 were recruited from the dialysis and kidney transplant Centers in Kerman City, Iran, from2007 to 2011. To assess the impacts of the investigated factors on the outcome, a cause-specific hazard model and competing risk models were fitted. Also, the cumulative incidence (CI) approach and sensitivity analysis were implemented. All of the analyses were performed using Stata software, V.12. RESULTS: The results of competing risk models showed that age and type of dialysis were associated with death (hazard ratio (HR)=1.03, p<0.001 and HR=1.65, p=0.011, respectively). In cause specific hazard model each year increase in age was associated with a 2% increase in the risk of death. Also, the types of dialysis were associated significantly with death (HR=1.93), and the effect of the type of dialysis was estimated as HR=1.51 (p=0.04) when we assumed that all patients who had experienced transplantation survived for the longest survival time. For those for whom receiving the transplantation was considered as death, the HR for the type of dialysis as well as the corresponding p-values were 1.82 and 0.001, respectively. CONCLUSION: Ignoring the competing risks of death due to ESRD, such as renal transplantation, in estimating the survival of these patients might lead to overestimation of the results.
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spelling pubmed-47008902016-01-13 Competing Risk Analyses of Patients with End-Stage Renal Disease Tabrizi, Reza Moosazadeh, Mahmood Sekhavati, Eghbal Jalali, Maryam Afshari, Mahdi Akbari, Maryam Baneshi, Mohammad Reza Electron Physician Original Article INTRODUCTION: Chronic kidney disease (CKD) is an important health problem that gradually leads to end-stage renal disease (ESRD). In ESRD patients, death due to other diseases or some events, such as renal transplantation (known as competing risks), would change the probability of observing the event of interest. The aim of this study was to estimate the survival of ESRD patients using competing risk analyses. METHODS: In this retrospective longitudinal study, 307 ESRD patients who were older than 20 were recruited from the dialysis and kidney transplant Centers in Kerman City, Iran, from2007 to 2011. To assess the impacts of the investigated factors on the outcome, a cause-specific hazard model and competing risk models were fitted. Also, the cumulative incidence (CI) approach and sensitivity analysis were implemented. All of the analyses were performed using Stata software, V.12. RESULTS: The results of competing risk models showed that age and type of dialysis were associated with death (hazard ratio (HR)=1.03, p<0.001 and HR=1.65, p=0.011, respectively). In cause specific hazard model each year increase in age was associated with a 2% increase in the risk of death. Also, the types of dialysis were associated significantly with death (HR=1.93), and the effect of the type of dialysis was estimated as HR=1.51 (p=0.04) when we assumed that all patients who had experienced transplantation survived for the longest survival time. For those for whom receiving the transplantation was considered as death, the HR for the type of dialysis as well as the corresponding p-values were 1.82 and 0.001, respectively. CONCLUSION: Ignoring the competing risks of death due to ESRD, such as renal transplantation, in estimating the survival of these patients might lead to overestimation of the results. Electronic physician 2015-11-20 /pmc/articles/PMC4700890/ /pubmed/26767098 http://dx.doi.org/10.19082/1458 Text en © 2015 The Authors This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) , 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 Original Article
Tabrizi, Reza
Moosazadeh, Mahmood
Sekhavati, Eghbal
Jalali, Maryam
Afshari, Mahdi
Akbari, Maryam
Baneshi, Mohammad Reza
Competing Risk Analyses of Patients with End-Stage Renal Disease
title Competing Risk Analyses of Patients with End-Stage Renal Disease
title_full Competing Risk Analyses of Patients with End-Stage Renal Disease
title_fullStr Competing Risk Analyses of Patients with End-Stage Renal Disease
title_full_unstemmed Competing Risk Analyses of Patients with End-Stage Renal Disease
title_short Competing Risk Analyses of Patients with End-Stage Renal Disease
title_sort competing risk analyses of patients with end-stage renal disease
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4700890/
https://www.ncbi.nlm.nih.gov/pubmed/26767098
http://dx.doi.org/10.19082/1458
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