Statistical Methods for Recurrent Event Analysis in Cohort Studies of CKD

被引：42

作者：

Yang, Wei ^{[1
,2
]}

Jepson, Christopher ^{[2
]}

Xie, Dawei ^{[1
,2
]}

Roy, Jason A. ^{[1
,2
]}

Shou, Haochang ^{[1
,2
]}

Hsu, Jesse Yenchih ^{[1
,2
]}

Anderson, Amanda Hyre ^{[1
,2
]}

Landis, J. Richard ^{[1
,2
]}

He, Jiang ^{[3
]}

Feldman, Harold I. ^{[1
,2
]}

机构：

[1] Univ Penn, Dept Biostat Epidemiol & Informat, Perelman Sch Med, 629 Blockley Hall,423 Guardian Dr, Philadelphia, PA 19104 USA

[2] Univ Penn, Ctr Clin Epidemiol & Biostat, Perelman Sch Med, Philadelphia, PA 19104 USA

[3] Tulane Univ, Dept Epidemiol, New Orleans, LA 70118 USA

来源：

CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY | 2017年 / 12卷 / 12期

基金：

美国国家卫生研究院;

关键词：

RENAL-INSUFFICIENCY COHORT; FAILURE TIME DATA; REGRESSION-ANALYSIS; HOSPITALIZATION; HEMODIALYSIS; RISK;

D O I：

10.2215/CJN.12841216

中图分类号：

R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];

学科分类号：

1002 ; 100201 ;

摘要：

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 reviewa number of statisticalmethods 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 themodels 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.

引用

页码：2066 / 2073

页数：8

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