Literature DB >> 33934950

Competing Risk Analysis: What Does It Mean and When Do We Need It in Orthopedics Research?

Hilal Maradit Kremers1, Katrina L Devick2, Dirk R Larson3, David G Lewallen4, Daniel J Berry4, Cynthia S Crowson5.   

Abstract

Most orthopedic studies involve survival analysis examining the time to an event of interest, such as a specific complication or revision surgery. Competing risks commonly arise in such studies when patients are at risk of more than one mutually exclusive event, such as death, or when the rate of an event depends on the rates of other competing events. In this article, we briefly describe the survival analysis censoring methodology, common fatal and nonfatal competing events, and define circumstances where standard survival analysis can fail in the setting of competing risks with real-world examples from orthopedics. Please visit the followinghttps://youtu.be/ifj_Mm3eGu8for a video that explains the highlights of the paper in practical terms.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  bias; censoring; competing risk; survival analysis; total joint arthroplasty

Mesh:

Year:  2021        PMID: 33934950      PMCID: PMC8478701          DOI: 10.1016/j.arth.2021.04.015

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.435


  8 in total

1.  Daily chlorhexidine bathing and hospital-acquired infection.

Authors:  Martin Wolkewitz; Stephan Harbarth; Jan Beyersmann
Journal:  N Engl J Med       Date:  2013-06-13       Impact factor: 91.245

2.  Competing Risk of Death When Comparing Tibial Implant Types in Total Knee Arthroplasty.

Authors:  Hilal Maradit Kremers; Walter K Kremers; Rafael J Sierra; David G Lewallen; Daniel J Berry
Journal:  J Bone Joint Surg Am       Date:  2016-04-06       Impact factor: 5.284

3.  Statistical analysis of failure times in total joint replacement.

Authors:  G Schwarzer; M Schumacher; T B Maurer; P E Ochsner
Journal:  J Clin Epidemiol       Date:  2001-10       Impact factor: 6.437

4.  Different competing risks models applied to data from the Australian Orthopaedic Association National Joint Replacement Registry.

Authors:  Marianne H Gillam; Amy Salter; Philip Ryan; Stephen E Graves
Journal:  Acta Orthop       Date:  2011-09-06       Impact factor: 3.717

Review 5.  Similar mortality rates in hip fracture patients over the past 31 years.

Authors:  Simran Mundi; Bharadwaj Pindiprolu; Nicole Simunovic; Mohit Bhandari
Journal:  Acta Orthop       Date:  2014-01-07       Impact factor: 3.717

6.  Are competing risks models appropriate to describe implant failure?

Authors:  Adrian Sayers; Jonathan T Evans; Michael R Whitehouse; Ashley W Blom
Journal:  Acta Orthop       Date:  2018-03-09       Impact factor: 3.717

7.  Different competing risks models for different questions may give similar results in arthroplasty registers in the presence of few events.

Authors:  Stéphanie Van Der Pas; Rob Nelissen; Marta Fiocco
Journal:  Acta Orthop       Date:  2018-02-01       Impact factor: 3.717

8.  What Is the Effect of Using a Competing-risks Estimator when Predicting Survivorship After Joint Arthroplasty: A Comparison of Approaches to Survivorship Estimation in a Large Registry.

Authors:  Alana R Cuthbert; Stephen E Graves; Lynne C Giles; Gary Glonek; Nicole Pratt
Journal:  Clin Orthop Relat Res       Date:  2021-02-01       Impact factor: 4.755

  8 in total
  1 in total

1.  Living With Survival Analysis in Orthopedics.

Authors:  Cynthia S Crowson; Dirk R Larson; Katrina L Devick; Elizabeth J Atkinson; Carly S Lundgreen; David G Lewallen; Daniel J Berry; Hilal Maradit Kremers
Journal:  J Arthroplasty       Date:  2021-04-22       Impact factor: 4.435

  1 in total

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