Literature DB >> 17634974

A competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazards.

Jan Beyersmann1, Markus Dettenkofer, Hartmut Bertz, Martin Schumacher.   

Abstract

After peripheral blood stem-cell transplantation, patients treated for severe haematologic diseases enter a critical phase (neutropenia). Analysis of bloodstream infection during neutropenia has to account for competing risks. Separate Cox analyses of all cause-specific hazards are the standard technique of choice, but are hard to interpret when the overall effects of covariates on the cumulative incidence function (CIF) are of interest. Proportional subdistribution hazards modelling of the subdistribution of the CIF is establishing itself as an interpretation-friendly alternative. We apply both methods and discuss their relative merits. Copyright (c) 2007 John Wiley & Sons, Ltd.

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Year:  2007        PMID: 17634974     DOI: 10.1002/sim.3006

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  23 in total

Review 1.  Applying competing risks regression models: an overview.

Authors:  Bernhard Haller; Georg Schmidt; Kurt Ulm
Journal:  Lifetime Data Anal       Date:  2012-09-26       Impact factor: 1.588

2.  Bias Due to Confounders for the Exposure-Competing Risk Relationship.

Authors:  Catherine R Lesko; Bryan Lau
Journal:  Epidemiology       Date:  2017-01       Impact factor: 4.822

3.  Joint Inference for Competing Risks Survival Data.

Authors:  Gang Li; Qing Yang
Journal:  J Am Stat Assoc       Date:  2016-10-18       Impact factor: 5.033

4.  Patient death as a censoring event or competing risk event in models of nursing home placement.

Authors:  Jeff M Szychowski; David L Roth; Olivio J Clay; Mary S Mittelman
Journal:  Stat Med       Date:  2010-02-10       Impact factor: 2.373

5.  Competing risk regression models for epidemiologic data.

Authors:  Bryan Lau; Stephen R Cole; Stephen J Gange
Journal:  Am J Epidemiol       Date:  2009-06-03       Impact factor: 4.897

6.  Evaluation of risk factors for cataract types in a competing risks framework.

Authors:  Robert J Glynn; Bernard Rosner; William G Christen
Journal:  Ophthalmic Epidemiol       Date:  2009 Mar-Apr       Impact factor: 1.648

7.  Development and validation of a coronary risk prediction model for older U.S. and European persons in the Cardiovascular Health Study and the Rotterdam Study.

Authors:  Michael T Koller; Maarten J G Leening; Marcel Wolbers; Ewout W Steyerberg; M G Myriam Hunink; Rotraut Schoop; Albert Hofman; Heiner C Bucher; Bruce M Psaty; Donald M Lloyd-Jones; Jacqueline C M Witteman
Journal:  Ann Intern Med       Date:  2012-09-18       Impact factor: 25.391

8.  Concordance for prognostic models with competing risks.

Authors:  Marcel Wolbers; Paul Blanche; Michael T Koller; Jacqueline C M Witteman; Thomas A Gerds
Journal:  Biostatistics       Date:  2014-02-02       Impact factor: 5.899

9.  Direct likelihood inference on the cause-specific cumulative incidence function: A flexible parametric regression modelling approach.

Authors:  Sarwar Islam Mozumder; Mark Rutherford; Paul Lambert
Journal:  Stat Med       Date:  2017-10-02       Impact factor: 2.373

10.  Importance of age of onset in pancreatic cancer kindreds.

Authors:  Kieran A Brune; Bryan Lau; Emily Palmisano; Marcia Canto; Michael G Goggins; Ralph H Hruban; Alison P Klein
Journal:  J Natl Cancer Inst       Date:  2010-01-12       Impact factor: 13.506

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