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When do we need competing risks methods for survival analysis in nephrology?

Noordzij, M., Leffondre, K., van Stralen, K. J., Zoccali, C., Dekker, F. W., Jager, K. J.·2013·Nephrology Dialysis Transplantation

Abstract

Survival analyses are commonly applied to study death or other events of interest. In such analyses, so-called competing risks may form an important problem. A competing risk is an event that either hinders the observation of the event of interest or modifies the chance that this event occurs. For example, when studying death on dialysis, receiving a kidney transplant is an event that competes with the event of interest. Conventional methods for survival analysis ignoring the competing event(s), such as the Kaplan-Meier method and standard Cox proportional hazards regression, may be inappropriate in the presence of competing risks, and alternative methods specifically designed for analysing competing risks data should then be applied. This problem deserves more attention in nephrology research and in the current article, we therefore explain the problem of competing risks in survival analysis and how using different techniques may affect study results.

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Metadata

Authors
Noordzij, M., Leffondre, K., van Stralen, K. J., Zoccali, C., Dekker, F. W., & Jager, K. J.
Venue
Nephrology Dialysis Transplantation
Published
2013-08-24
Volume
28
Issue
11
Pages
2670-2677
ISSN
  • 0931-0509 (ISSN-L)
  • 1460-2385
OpenAlex
W2145755811
Cited by
669
References
2
FWCI
22.08
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: When do we need competing risks methods for survival analysis in nephrology? https://app.cochat.ai/papers/10.1093/ndt/gft355
The paper
Noordzij, M., Leffondre, K., van Stralen, K. J., Zoccali, C., Dekker, F. W., & Jager, K. J. (2013). When do we need competing risks methods for survival analysis in nephrology? Nephrology Dialysis Transplantation. https://doi.org/10.1093/ndt/gft355

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.