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Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art

BACKGROUND: Chronic kidney disease (CKD) is a progressive and usually irreversible disease. Different types of outcomes are of interest in the course of CKD such as time-to-dialysis, transplantation or decline of the glomerular filtration rate (GFR). Statistical analyses aiming at investigating the...

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Autores principales: Boucquemont, Julie, Heinze, Georg, Jager, Kitty J, Oberbauer, Rainer, Leffondre, Karen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004351/
https://www.ncbi.nlm.nih.gov/pubmed/24628838
http://dx.doi.org/10.1186/1471-2369-15-45
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author Boucquemont, Julie
Heinze, Georg
Jager, Kitty J
Oberbauer, Rainer
Leffondre, Karen
author_facet Boucquemont, Julie
Heinze, Georg
Jager, Kitty J
Oberbauer, Rainer
Leffondre, Karen
author_sort Boucquemont, Julie
collection PubMed
description BACKGROUND: Chronic kidney disease (CKD) is a progressive and usually irreversible disease. Different types of outcomes are of interest in the course of CKD such as time-to-dialysis, transplantation or decline of the glomerular filtration rate (GFR). Statistical analyses aiming at investigating the association between these outcomes and risk factors raise a number of methodological issues. The objective of this study was to give an overview of these issues and to highlight some statistical methods that can address these topics. METHODS: A literature review of statistical methods published between 2002 and 2012 to investigate risk factors of CKD outcomes was conducted within the Scopus database. The results of the review were used to identify important methodological issues as well as to discuss solutions for each type of CKD outcome. RESULTS: Three hundred and four papers were selected. Time-to-event outcomes were more often investigated than quantitative outcome variables measuring kidney function over time. The most frequently investigated events in survival analyses were all-cause death, initiation of kidney replacement therapy, and progression to a specific value of GFR. While competing risks were commonly accounted for, interval censoring was rarely acknowledged when appropriate despite existing methods. When the outcome of interest was the quantitative decline of kidney function over time, standard linear models focussing on the slope of GFR over time were almost as often used as linear mixed models which allow various numbers of repeated measurements of kidney function per patient. Informative dropout was accounted for in some of these longitudinal analyses. CONCLUSIONS: This study provides a broad overview of the statistical methods used in the last ten years for investigating risk factors of CKD progression, as well as a discussion of their limitations. Some existing potential alternatives that have been proposed in the context of CKD or in other contexts are also highlighted.
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spelling pubmed-40043512014-04-30 Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art Boucquemont, Julie Heinze, Georg Jager, Kitty J Oberbauer, Rainer Leffondre, Karen BMC Nephrol Research Article BACKGROUND: Chronic kidney disease (CKD) is a progressive and usually irreversible disease. Different types of outcomes are of interest in the course of CKD such as time-to-dialysis, transplantation or decline of the glomerular filtration rate (GFR). Statistical analyses aiming at investigating the association between these outcomes and risk factors raise a number of methodological issues. The objective of this study was to give an overview of these issues and to highlight some statistical methods that can address these topics. METHODS: A literature review of statistical methods published between 2002 and 2012 to investigate risk factors of CKD outcomes was conducted within the Scopus database. The results of the review were used to identify important methodological issues as well as to discuss solutions for each type of CKD outcome. RESULTS: Three hundred and four papers were selected. Time-to-event outcomes were more often investigated than quantitative outcome variables measuring kidney function over time. The most frequently investigated events in survival analyses were all-cause death, initiation of kidney replacement therapy, and progression to a specific value of GFR. While competing risks were commonly accounted for, interval censoring was rarely acknowledged when appropriate despite existing methods. When the outcome of interest was the quantitative decline of kidney function over time, standard linear models focussing on the slope of GFR over time were almost as often used as linear mixed models which allow various numbers of repeated measurements of kidney function per patient. Informative dropout was accounted for in some of these longitudinal analyses. CONCLUSIONS: This study provides a broad overview of the statistical methods used in the last ten years for investigating risk factors of CKD progression, as well as a discussion of their limitations. Some existing potential alternatives that have been proposed in the context of CKD or in other contexts are also highlighted. BioMed Central 2014-03-14 /pmc/articles/PMC4004351/ /pubmed/24628838 http://dx.doi.org/10.1186/1471-2369-15-45 Text en Copyright © 2014 Boucquemont et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research Article
Boucquemont, Julie
Heinze, Georg
Jager, Kitty J
Oberbauer, Rainer
Leffondre, Karen
Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
title Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
title_full Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
title_fullStr Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
title_full_unstemmed Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
title_short Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
title_sort regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004351/
https://www.ncbi.nlm.nih.gov/pubmed/24628838
http://dx.doi.org/10.1186/1471-2369-15-45
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