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When do we need competing risks methods for survival analysis in nephrology?

Nephrology Dialysis Transplantation · 2013 · Vol. 28(11) · pp. 2670–2677
Marlies NoordzijKaren LeffondréKarlijn J. van StralenCarmine ZoccaliFriedo W. DekkerKitty J. Jager

Abstract

Survival analyses are commonly applied to study death or other events of interest. In such analyses, so-called competing risks may form an important problem. A competing risk is an event that either hinders the observation of the event of interest or modifies the chance that this event occurs. For example, when studying death on dialysis, receiving a kidney transplant is an event that competes with the event of interest. Conventional methods for survival analysis ignoring the competing event(s), such as the Kaplan-Meier method and standard Cox proportional hazards regression, may be inappropriate in the presence of competing risks, and alternative methods specifically designed for analysing competing risks data should then be applied. This problem deserves more attention in nephrology research and in the current article, we therefore explain the problem of competing risks in survival analysis and how using different techniques may affect study results.

Statistical Methods and InferenceHealth Systems, Economic Evaluations, Quality of LifeInsurance, Mortality, Demography, Risk ManagementMedicineProportional hazards modelEvent (particle physics)Survival analysisNephrologyDialysisIntensive care medicineInternal medicineRisk analysis (engineering)

MeSH terms

Data Interpretation, StatisticalRenal DialysisHumansNephrologyModels, StatisticalSurvival Analysis
Citations
668
FWCI
25.41
field-weighted impact
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25
Percentile
100%
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Citations per year
References
A Proportional Hazards Model for the Subdistribution of a Competing Risk
Journal of the American Statistical Association · 1999 · 13,371 citations
Competing risks in epidemiology: possibilities and pitfalls
International Journal of Epidemiology · 2012 · 934 citations
Competing Risk Regression Models for Epidemiologic Data
American Journal of Epidemiology · 2009 · 1,382 citations
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When do we need competing risks methods for survival analysis in nephrology? · Scinovex