Statistical methods for recurrent event analysis in cohort studies of CKD

Chronic Renal Insufficiency Cohort (CRIC) Study Investigators

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Cardiovascular events, such as hospitalizations because of congestive heart failure, often occur repeatedly in patients with CKD. Many studies focus on analyses of the first occurrence of these events, and discard subsequent information. In this article, we review a number of statistical methods for analyzing ordered recurrent events of the same type, including Poisson regression and three commonly used survival models that are extensions of Cox proportional hazards regression. We illustrate the models by analyzing data from the Chronic Renal Insufficiency Cohort Study to identify risk factors for congestive heart failure hospitalizations in patients with CKD. We show that recurrent event analyses provide additional insights about the data compared with a standard survival analysis of time to the first event.

Original languageEnglish (US)
Pages (from-to)2066-2073
Number of pages8
JournalClinical Journal of the American Society of Nephrology
Volume12
Issue number12
DOIs
StatePublished - Dec 7 2017

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Critical Care and Intensive Care Medicine
  • Nephrology
  • Transplantation

Keywords

  • Chronic
  • Chronic kidney disease
  • Cohort studies
  • Cox proportional hazards model
  • Heart failure
  • Hospitalization
  • Humans
  • Poisson regression
  • Recurrent event
  • Renal insufficiency
  • Risk factors
  • Survival analysis

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