Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/38807
Title: | Bias by censoring for competing events in survival analysis | Authors: | Coemans, Maarten VERBEKE, Geert Doehler, Bernd Suesal, Caner Naesens, Maarten |
Issue Date: | 2022 | Publisher: | BMJ PUBLISHING GROUP | Source: | BMJ-British Medical Journal, 378 (Art N° e071349) | Abstract: | 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. | Notes: | Naesens, M (corresponding author), Katholieke Univ Leuven, Dept Microbiol Immunol & Transplantat, Leuven, Belgium. maarten.naesens@kuleuven.be |
Keywords: | Bias;Humans;Survival Analysis | Document URI: | http://hdl.handle.net/1942/38807 | ISSN: | 0959-535X | e-ISSN: | 1756-1833 | DOI: | 10.1136/bmj-2021-071349 | ISI #: | 000860470700004 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2023 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Bias by censoring for competing events in survival analysis.pdf Restricted Access | Published version | 933.11 kB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.