Application of competing risks analysis improved prognostic assessment of patients with decompensated chronic heart failure and reduced left ventricular ejection fraction

Domenico Scrutinio, Pietro Guida, Andrea Passantino, Enrico Ammirati, Fabrizio Oliva, Rocco Lagioia, Maria Frigerio

Research output: Contribution to journalArticle

Abstract

OBJECTIVE: The Kaplan-Meier method may overestimate absolute mortality risk (AMR) in the presence of competing risks. Urgent heart transplantation (UHT) and ventricular assist device implantation (VADi) are important competing events in heart failure. We sought to quantify the extent of bias of the Kaplan-Meier method in estimating AMR in the presence of competing events and to analyze the effect of covariates on the hazard for death and competing events in the clinical model of decompensated chronic heart failure with reduced ejection fraction (DCHFrEF).

STUDY DESIGN AND SETTING: We studied 683 patients. We used the cumulative incidence function (CIF) to estimate the AMR at 1 year. CIF estimate was compared with the Kaplan-Meier estimate. The Fine-Gray subdistribution hazard analysis was used to assess the effect of covariates on the hazard for death and UHT/VADi.

RESULTS: The Kaplan-Meier estimate of the AMR was 0.272, whereas the CIF estimate was 0.246. The difference was more pronounced in the patient subgroup with advanced DCHF (0.424 vs. 0.338). The Fine-Gray subdistribution hazard analysis revealed that established risk markers have qualitatively different effects on the incidence of death or UHT/VADi.

CONCLUSION: Competing risks analysis allows more accurately estimating AMR and better understanding the association between covariates and major outcomes in DCHFrEF.

Original languageEnglish
Pages (from-to)31-39
Number of pages9
JournalJournal of Clinical Epidemiology
Volume103
DOIs
Publication statusPublished - Nov 2018

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Stroke Volume
Heart Failure
Heart-Assist Devices
Heart Transplantation
Mortality
Incidence
Kaplan-Meier Estimate

Cite this

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title = "Application of competing risks analysis improved prognostic assessment of patients with decompensated chronic heart failure and reduced left ventricular ejection fraction",
abstract = "OBJECTIVE: The Kaplan-Meier method may overestimate absolute mortality risk (AMR) in the presence of competing risks. Urgent heart transplantation (UHT) and ventricular assist device implantation (VADi) are important competing events in heart failure. We sought to quantify the extent of bias of the Kaplan-Meier method in estimating AMR in the presence of competing events and to analyze the effect of covariates on the hazard for death and competing events in the clinical model of decompensated chronic heart failure with reduced ejection fraction (DCHFrEF).STUDY DESIGN AND SETTING: We studied 683 patients. We used the cumulative incidence function (CIF) to estimate the AMR at 1 year. CIF estimate was compared with the Kaplan-Meier estimate. The Fine-Gray subdistribution hazard analysis was used to assess the effect of covariates on the hazard for death and UHT/VADi.RESULTS: The Kaplan-Meier estimate of the AMR was 0.272, whereas the CIF estimate was 0.246. The difference was more pronounced in the patient subgroup with advanced DCHF (0.424 vs. 0.338). The Fine-Gray subdistribution hazard analysis revealed that established risk markers have qualitatively different effects on the incidence of death or UHT/VADi.CONCLUSION: Competing risks analysis allows more accurately estimating AMR and better understanding the association between covariates and major outcomes in DCHFrEF.",
author = "Domenico Scrutinio and Pietro Guida and Andrea Passantino and Enrico Ammirati and Fabrizio Oliva and Rocco Lagioia and Maria Frigerio",
note = "Copyright {\circledC} 2018 Elsevier Inc. All rights reserved.",
year = "2018",
month = "11",
doi = "10.1016/j.jclinepi.2018.07.006",
language = "English",
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TY - JOUR

T1 - Application of competing risks analysis improved prognostic assessment of patients with decompensated chronic heart failure and reduced left ventricular ejection fraction

AU - Scrutinio, Domenico

AU - Guida, Pietro

AU - Passantino, Andrea

AU - Ammirati, Enrico

AU - Oliva, Fabrizio

AU - Lagioia, Rocco

AU - Frigerio, Maria

N1 - Copyright © 2018 Elsevier Inc. All rights reserved.

PY - 2018/11

Y1 - 2018/11

N2 - OBJECTIVE: The Kaplan-Meier method may overestimate absolute mortality risk (AMR) in the presence of competing risks. Urgent heart transplantation (UHT) and ventricular assist device implantation (VADi) are important competing events in heart failure. We sought to quantify the extent of bias of the Kaplan-Meier method in estimating AMR in the presence of competing events and to analyze the effect of covariates on the hazard for death and competing events in the clinical model of decompensated chronic heart failure with reduced ejection fraction (DCHFrEF).STUDY DESIGN AND SETTING: We studied 683 patients. We used the cumulative incidence function (CIF) to estimate the AMR at 1 year. CIF estimate was compared with the Kaplan-Meier estimate. The Fine-Gray subdistribution hazard analysis was used to assess the effect of covariates on the hazard for death and UHT/VADi.RESULTS: The Kaplan-Meier estimate of the AMR was 0.272, whereas the CIF estimate was 0.246. The difference was more pronounced in the patient subgroup with advanced DCHF (0.424 vs. 0.338). The Fine-Gray subdistribution hazard analysis revealed that established risk markers have qualitatively different effects on the incidence of death or UHT/VADi.CONCLUSION: Competing risks analysis allows more accurately estimating AMR and better understanding the association between covariates and major outcomes in DCHFrEF.

AB - OBJECTIVE: The Kaplan-Meier method may overestimate absolute mortality risk (AMR) in the presence of competing risks. Urgent heart transplantation (UHT) and ventricular assist device implantation (VADi) are important competing events in heart failure. We sought to quantify the extent of bias of the Kaplan-Meier method in estimating AMR in the presence of competing events and to analyze the effect of covariates on the hazard for death and competing events in the clinical model of decompensated chronic heart failure with reduced ejection fraction (DCHFrEF).STUDY DESIGN AND SETTING: We studied 683 patients. We used the cumulative incidence function (CIF) to estimate the AMR at 1 year. CIF estimate was compared with the Kaplan-Meier estimate. The Fine-Gray subdistribution hazard analysis was used to assess the effect of covariates on the hazard for death and UHT/VADi.RESULTS: The Kaplan-Meier estimate of the AMR was 0.272, whereas the CIF estimate was 0.246. The difference was more pronounced in the patient subgroup with advanced DCHF (0.424 vs. 0.338). The Fine-Gray subdistribution hazard analysis revealed that established risk markers have qualitatively different effects on the incidence of death or UHT/VADi.CONCLUSION: Competing risks analysis allows more accurately estimating AMR and better understanding the association between covariates and major outcomes in DCHFrEF.

U2 - 10.1016/j.jclinepi.2018.07.006

DO - 10.1016/j.jclinepi.2018.07.006

M3 - Article

VL - 103

SP - 31

EP - 39

JO - Journal of Clinical Epidemiology

JF - Journal of Clinical Epidemiology

SN - 0895-4356

ER -