MétaCan
← all works

Introduction to the Analysis of Survival Data in the Presence of Competing Risks

2016· article· en· 2,536 citations· W2264767503 on OpenAlex· 10.1161/circulationaha.115.017719

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Abstract

Competing risks occur frequently in the analysis of survival data. A competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. In a study examining time to death attributable to cardiovascular causes, death attributable to noncardiovascular causes is a competing risk. When estimating the crude incidence of outcomes, analysts should use the cumulative incidence function, rather than the complement of the Kaplan-Meier survival function. The use of the Kaplan-Meier survival function results in estimates of incidence that are biased upward, regardless of whether the competing events are independent of one another. When fitting regression models in the presence of competing risks, researchers can choose from 2 different families of models: modeling the effect of covariates on the cause-specific hazard of the outcome or modeling the effect of covariates on the cumulative incidence function. The former allows one to estimate the effect of the covariates on the rate of occurrence of the outcome in those subjects who are currently event free. The latter allows one to estimate the effect of covariates on the absolute risk of the outcome over time. The former family of models may be better suited for addressing etiologic questions, whereas the latter model may be better suited for estimating a patient's clinical prognosis. We illustrate the application of these methods by examining cause-specific mortality in patients hospitalized with heart failure. Statistical software code in both R and SAS is provided.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
Circulation
Topic
Advanced Causal Inference Techniques
Field
Mathematics
Canadian institutions
University of TorontoUniversity Health NetworkInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Funders
Canadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative SciencesHeart and Stroke Foundation of Canada
Keywords
CovariateMedicineProportional hazards modelSurvival analysisCumulative incidenceIncidence (geometry)Survival functionEvent (particle physics)StatisticsHazard ratioOutcome (game theory)HazardDemographyAccelerated failure time modelEconometricsConfidence intervalInternal medicineCohortMathematics
Has abstract in OpenAlex
yes