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Competing risks in epidemiology: possibilities and pitfalls
Open accessAbstract
BACKGROUND: In studies of all-cause mortality, the fundamental epidemiological concepts of rate and risk are connected through a well-defined one-to-one relation. An important consequence of this relation is that regression models such as the proportional hazards model that are defined through the hazard (the rate) immediately dictate how the covariates relate to the survival function (the risk). METHODS: This introductory paper reviews the concepts of rate and risk and their one-to-one relation in all-cause mortality studies and introduces the analogous concepts of rate and risk in the context of competing risks, the cause-specific hazard and the cause-specific cumulative incidence function. RESULTS: The key feature of competing risks is that the one-to-one correspondence between cause-specific hazard and cumulative incidence, between rate and risk, is lost. This fact has two important implications. First, the naïve Kaplan-Meier that takes the competing events as censored observations, is biased. Secondly, the way in which covariates are associated with the cause-specific hazards may not coincide with the way these covariates are associated with the cumulative incidence. An example with relapse and non-relapse mortality as competing risks in a stem cell transplantation study is used for illustration. CONCLUSION: The two implications of the loss of one-to-one correspondence between cause-specific hazard and cumulative incidence should be kept in mind when deciding on how to make inference in a competing risks situation.
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“The design of our study (an incidence surveillance system), the possible presence of competitive causes of death and the limited period of observation prevent statistical inferences on the association between exposure and time to event (age or latency).39 40”
From Malignant mesothelioma due to non-occupational asbestos exposure from the Italian national surveillance system (ReNaM): epidemiology and public health issues (2015) · cites this paper as [40]
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Metadata
- Authors
- Andersen, P. K., Geskus, R. B., de Witte, T., & Putter, H.
- Affiliations
- University of Copenhagen (DK)
- Amsterdam UMC Location University of Amsterdam (NL)
- Leiden University Medical Center (NL)
- Corresponding author
- Putter, Hein
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-01-09
- Volume
- 41
- Issue
- 3
- Pages
- 861-870
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- PMC
- PMC3396320
- OpenAlex
- W2154117702
- Semantic Scholar
- fad89d6c4d4b7b80df8a26be5a2c8e1dd54eec29
- Cited by
- 985
- References
- 18
- Citations by year
- 2026: 83 · 2025: 59 · 2024: 78 · 2023: 75 · 2022: 71 · 2021: 66 · 2020: 102 · 2019: 88 · 2018: 77 · 2017: 77 · 2016: 73 · 2015: 47 · 2014: 51 · 2013: 29 · 2012: 9
- FWCI
- 41.50
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Epidemiology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Funders
- U.S. Public Health Service (R01-54706-12)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Keywords
- competing risks, all-cause mortality, cause-specific hazard, cumulative incidence function, stem cell transplantation
- MeSH terms
- Humans, Models, Theoretical, Mortality, Survival Analysis, Epidemiologic Studies, Risk Assessment
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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