On the relation between the cause‐specific hazard and the subdistribution rate for competing risks data: The Fine–Gray model revisited

The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistr...

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Published inBiometrical journal Vol. 62; no. 3; pp. 790 - 807
Main Authors Putter, Hein, Schumacher, Martin, van Houwelingen, Hans C.
Format Journal Article
LanguageEnglish
Published Germany Wiley - VCH Verlag GmbH & Co. KGaA 01.05.2020
John Wiley and Sons Inc
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Abstract The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistribution hazard and the extended risk sets, where subjects who failed of the competing risk remain in the risk set, are generally perceived as unnatural . One could say it is somewhat of a riddle why the Fine–Gray approach yields valid inference. To take away these uneasy feelings, we explore the link between the Fine–Gray and cause‐specific approaches in more detail. We introduce the reduction factor as representing the proportion of subjects in the Fine–Gray risk set that has not yet experienced a competing event. In the presence of covariates, the dependence of the reduction factor on a covariate gives information on how the effect of the covariate on the cause‐specific hazard and the subdistribution hazard relate. We discuss estimation and modeling of the reduction factor, and show how they can be used in various ways to estimate cumulative incidences, given the covariates. Methods are illustrated on data of the European Society for Blood and Marrow Transplantation.
AbstractList The Fine-Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistribution hazard and the extended risk sets, where subjects who failed of the competing risk remain in the risk set, are generally perceived as unnatural . One could say it is somewhat of a riddle why the Fine-Gray approach yields valid inference. To take away these uneasy feelings, we explore the link between the Fine-Gray and cause-specific approaches in more detail. We introduce the reduction factor as representing the proportion of subjects in the Fine-Gray risk set that has not yet experienced a competing event. In the presence of covariates, the dependence of the reduction factor on a covariate gives information on how the effect of the covariate on the cause-specific hazard and the subdistribution hazard relate. We discuss estimation and modeling of the reduction factor, and show how they can be used in various ways to estimate cumulative incidences, given the covariates. Methods are illustrated on data of the European Society for Blood and Marrow Transplantation.
The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistribution hazard and the extended risk sets, where subjects who failed of the competing risk remain in the risk set, are generally perceived as unnatural . One could say it is somewhat of a riddle why the Fine–Gray approach yields valid inference. To take away these uneasy feelings, we explore the link between the Fine–Gray and cause‐specific approaches in more detail. We introduce the reduction factor as representing the proportion of subjects in the Fine–Gray risk set that has not yet experienced a competing event. In the presence of covariates, the dependence of the reduction factor on a covariate gives information on how the effect of the covariate on the cause‐specific hazard and the subdistribution hazard relate. We discuss estimation and modeling of the reduction factor, and show how they can be used in various ways to estimate cumulative incidences, given the covariates. Methods are illustrated on data of the European Society for Blood and Marrow Transplantation.
Abstract The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistribution hazard and the extended risk sets, where subjects who failed of the competing risk remain in the risk set, are generally perceived as unnatural . One could say it is somewhat of a riddle why the Fine–Gray approach yields valid inference. To take away these uneasy feelings, we explore the link between the Fine–Gray and cause‐specific approaches in more detail. We introduce the reduction factor as representing the proportion of subjects in the Fine–Gray risk set that has not yet experienced a competing event. In the presence of covariates, the dependence of the reduction factor on a covariate gives information on how the effect of the covariate on the cause‐specific hazard and the subdistribution hazard relate. We discuss estimation and modeling of the reduction factor, and show how they can be used in various ways to estimate cumulative incidences, given the covariates. Methods are illustrated on data of the European Society for Blood and Marrow Transplantation.
Author Schumacher, Martin
Putter, Hein
van Houwelingen, Hans C.
AuthorAffiliation 1 Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
2 Institute for Medical Biometry and Statistics Faculty of Medicine and Medical Center University of Freiburg Freiburg im Breisgau Germany
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Cites_doi 10.1093/ije/dyr213
10.1007/978-1-4757-3294-8
10.1007/978-1-4612-4348-9
10.1002/sim.4385
10.1111/biom.12061
10.1002/sim.4780122406
10.1191/0962280202sm281ra
10.1201/b18695
10.1002/bimj.200900076
10.1002/sim.5773
10.1002/sim.3786
10.1002/sim.2600
10.1080/01621459.1999.10474144
10.2307/2530374
10.1002/sim.3844
10.1016/j.cmpb.2010.01.001
10.1002/sim.2712
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Issue 3
Keywords competing risks
subdistribution hazard
cumulative incidence
proportional hazards
cause-specific hazard
Language English
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References 2010; 99
1993; 12
2013b; 69
2012
1978; 34
2011
2013; 32
2000
2010; 29
2013a; 29
2002; 11
1993
2015
2014
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1999; 94
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2007; 26
e_1_2_9_20_1
Beyersmann J. (e_1_2_9_6_1) 2011
Beyersmann J. (e_1_2_9_7_1) 2013
Nicolaie M. A. (e_1_2_9_16_1) 2013; 29
e_1_2_9_11_1
e_1_2_9_22_1
e_1_2_9_10_1
e_1_2_9_21_1
e_1_2_9_12_1
Gray B. (e_1_2_9_13_1) 2014
e_1_2_9_8_1
e_1_2_9_5_1
e_1_2_9_4_1
e_1_2_9_3_1
e_1_2_9_2_1
e_1_2_9_9_1
e_1_2_9_15_1
e_1_2_9_17_1
Houwelingen H. (e_1_2_9_14_1) 2012
e_1_2_9_19_1
e_1_2_9_18_1
References_xml – year: 2011
– volume: 94
  start-page: 496
  year: 1999
  end-page: 509
  article-title: A proportional hazards model for the subdistribution of a competing risk
  publication-title: Journal of the American Statistical Association
– volume: 11
  start-page: 203
  issue: 2
  year: 2002
  end-page: 215
  article-title: Competing risks as a multi‐state model
  publication-title: Statistical Methods in Medical Research
– volume: 29
  start-page: 1190
  year: 2013a
  end-page: 1205
  article-title: Vertical modeling: A pattern mixture approach for competing risks modeling
  publication-title: Statistics in Medicine
– volume: 12
  start-page: 2285
  year: 1993
  end-page: 2303
  article-title: Relative risk, risk difference and rate difference models for sparse stratified data: A pseudo likelihood approach
  publication-title: Statistics in Medicine
– volume: 32
  start-page: 3089
  year: 2013
  end-page: 3101
  article-title: Comparing predictions among competing risks models with time‐dependent covariates
  publication-title: Statistics in Medicine
– volume: 52
  start-page: 138
  year: 2010
  end-page: 158
  article-title: Competing risks and time‐dependent covariates
  publication-title: Biometrical Journal
– volume: 31
  start-page: 1074
  year: 2012
  end-page: 1088
  article-title: Interpretability and importance of functionals in competing risks and multistate models
  publication-title: Statistics in Medicine
– volume: 29
  start-page: 875
  year: 2010
  end-page: 884
  article-title: Proportional subdistribution hazards modeling offers a summary analysis, even if misspecified
  publication-title: Statistics in Medicine
– volume: 34
  start-page: 541
  issue: 4
  year: 1978
  end-page: 554
  article-title: The analysis of failure times in the presence of competing risks
  publication-title: Biometrics
– volume: 69
  start-page: 1043
  year: 2013b
  end-page: 1052
  article-title: Dynamic pseudo‐observations: A robust approach to dynamic prediction in competing risks
  publication-title: Biometrics
– year: 2000
– volume: 99
  start-page: 261
  year: 2010
  end-page: 274
  article-title: The mstate package for estimation and prediction in non‐ and semi‐parametric multi‐state and competing risks models
  publication-title: Computer Methods and Programs in Biomedicine
– volume: 26
  start-page: 965
  year: 2007
  end-page: 974
  article-title: Misspecified regression model for the subdistribution hazard of a competing risk
  publication-title: Statistics in Medicine
– volume: 41
  start-page: 861
  issue: 3
  year: 2012
  end-page: 870
  article-title: Competing risks in epidemiology: Possibilities and pitfalls
  publication-title: International Journal of Epidemiology
– start-page: 153
  year: 2013
  end-page: 172
– year: 1993
– year: 2014
– volume: 26
  start-page: 2389
  issue: 11
  year: 2007
  end-page: 2430
  article-title: Tutorial in biostatistics: Competing risks and multi‐state models
  publication-title: Statistics in Medicine
– year: 2015
– year: 2012
– ident: e_1_2_9_4_1
  doi: 10.1093/ije/dyr213
– ident: e_1_2_9_21_1
  doi: 10.1007/978-1-4757-3294-8
– ident: e_1_2_9_3_1
  doi: 10.1007/978-1-4612-4348-9
– ident: e_1_2_9_5_1
  doi: 10.1002/sim.4385
– ident: e_1_2_9_17_1
  doi: 10.1111/biom.12061
– ident: e_1_2_9_20_1
  doi: 10.1002/sim.4780122406
– ident: e_1_2_9_2_1
  doi: 10.1191/0962280202sm281ra
– start-page: 153
  volume-title: Handbook of Survival Analysis
  year: 2013
  ident: e_1_2_9_7_1
  contributor:
    fullname: Beyersmann J.
– ident: e_1_2_9_11_1
  doi: 10.1201/b18695
– ident: e_1_2_9_8_1
  doi: 10.1002/bimj.200900076
– ident: e_1_2_9_9_1
  doi: 10.1002/sim.5773
– ident: e_1_2_9_12_1
  doi: 10.1002/sim.3786
– ident: e_1_2_9_15_1
  doi: 10.1002/sim.2600
– ident: e_1_2_9_10_1
  doi: 10.1080/01621459.1999.10474144
– volume-title: Dynamic prediction in clinical survival analysis
  year: 2012
  ident: e_1_2_9_14_1
  contributor:
    fullname: Houwelingen H.
– volume-title: Competing risks and multistate models with R
  year: 2011
  ident: e_1_2_9_6_1
  contributor:
    fullname: Beyersmann J.
– volume-title: cmprsk: Subdistribution analysis of competing risks
  year: 2014
  ident: e_1_2_9_13_1
  contributor:
    fullname: Gray B.
– ident: e_1_2_9_18_1
  doi: 10.2307/2530374
– volume: 29
  start-page: 1190
  year: 2013
  ident: e_1_2_9_16_1
  article-title: Vertical modeling: A pattern mixture approach for competing risks modeling
  publication-title: Statistics in Medicine
  doi: 10.1002/sim.3844
  contributor:
    fullname: Nicolaie M. A.
– ident: e_1_2_9_22_1
  doi: 10.1016/j.cmpb.2010.01.001
– ident: e_1_2_9_19_1
  doi: 10.1002/sim.2712
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Snippet The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that...
The Fine-Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that...
Abstract The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling...
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StartPage 790
SubjectTerms cause‐specific hazard
competing risks
cumulative incidence
Hazards
proportional hazards
Reduction
Research Paper
Research Papers
Risk perception
subdistribution hazard
Transplantation
Title On the relation between the cause‐specific hazard and the subdistribution rate for competing risks data: The Fine–Gray model revisited
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fbimj.201800274
https://www.ncbi.nlm.nih.gov/pubmed/32128860
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