Journal
BMJ-BRITISH MEDICAL JOURNAL
Volume 378, Issue -, Pages -Publisher
BMJ PUBLISHING GROUP
DOI: 10.1136/bmj-2022-071349
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Funding
- Fonds Wetenschappelijk Onderzoek (Research Foundation-Flanders)
- Applied Biomedical Research with a Primary Social Finality
- Fonds Wetenschappelijk Onderzoek (Research Foundation-Flanders) [IWT.150199]
- [1844019N]
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Competing risks in survival analysis can lead to biased cumulative incidence estimators. Competing risks methods, such as the Aalen-Johansen method and the Fine and Gray model, can alleviate this bias and should be preferred over traditional methods.
In survival analysis, competing events preclude the occurrence of the event of interest. The censoring of competing events is common in medical studies but leads to biased cumulative incidence estimators. Competing risks methods, such as the non-parametric Aalen-Johansen method or the semi -parametric Fine and Gray model, alleviate this bias and should be preferred above the Kaplan-Meier method and the Cox model, respectively. As an illustrative example, in a large European cohort, we report on the differences in the cumulative incidence estimates of graft failure after kidney transplantation, caused by censoring for recipient death.
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