Identification of a Multistate Continuous-Time Nonhomogeneous Markov Chain Model for Patients with Decreased Renal Function

Begun, Alexander; Icks, Andrea; Waldeyer, Regina; Landwehr, Sandra; Koch, Michael; Giani, Guido

doi:10.1177/0272989x12466731

Cited by 20 publications

(13 citation statements)

References 30 publications

(47 reference statements)

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“…The CKD model builds on the framework of previous models [17][18][19][20][21][22] ( Figure 1). The health states for CKD are defined following the National Kidney Foundation K/DOQI guidelines.…”

Section: Methodsmentioning

confidence: 99%

Cost‐effectiveness of elbasvir/grazoprevir use in treatment‐naive and treatment‐experienced patients with hepatitis C virus genotype 1 infection and chronic kidney disease in the United States

Elbasha

Greaves

Roth

et al. 2016

Journal of Viral Hepatitis

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SummaryAmong patients with chronic kidney disease (CKD) in the United States, HCV infection causes significant morbidity and mortality and results in substantial healthcare costs. A once-daily oral regimen of elbasvir/grazoprevir (EBR/GZR) for 12 weeks was found to be a safe and efficacious treatment for HCV in patients with CKD. We evaluated the cost-effectiveness of EBR/GZR in treatment-naïve and treatment-experienced CKD pa-

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Section: Methodsmentioning

confidence: 99%

Cost‐effectiveness of elbasvir/grazoprevir use in treatment‐naive and treatment‐experienced patients with hepatitis C virus genotype 1 infection and chronic kidney disease in the United States

Elbasha

Greaves

Roth

et al. 2016

Journal of Viral Hepatitis

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“…For example, Begun et al recently considered a six-state model for interval-censored data, where the states were CKD stages 3, 4 and 5, dialysis, transplant, and death [27]. Foucher et al proposed four-state and five-state models for the study of kidney transplant evolution [4,28], considering interval-censored data since intermediate states were defined on creatinine clearance and/or proteinuria levels.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2014

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BackgroundChronic 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.MethodsA 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.ResultsThree 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.ConclusionsThis 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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“…Multi-state model based on Markov processes is often used to model and analyze the course of CKD. 21,22 The rates of transition between different stages can be estimated. Also, covariates can be fitted to the transition rates.…”

Section: Discussionmentioning

confidence: 99%

A Multi-State Markov Model for the Progression of Chronic Kidney Disease

Grover¹,

Sabharwal²,

Kumar³

et al. 2019

Turkiye Klinikleri J Biostat

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Identification of a Multistate Continuous-Time Nonhomogeneous Markov Chain Model for Patients with Decreased Renal Function

Abstract: In summary, modeling may help to quantify disease progression and its predictors when only partially observable prospective data are available.

Cited by 20 publications

References 30 publications

Cost‐effectiveness of elbasvir/grazoprevir use in treatment‐naive and treatment‐experienced patients with hepatitis C virus genotype 1 infection and chronic kidney disease in the United States

Cost‐effectiveness of elbasvir/grazoprevir use in treatment‐naive and treatment‐experienced patients with hepatitis C virus genotype 1 infection and chronic kidney disease in the United States

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

A Multi-State Markov Model for the Progression of Chronic Kidney Disease

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