Data-driven simulations to assess the impact of study imperfections in time-to-event analyses

Abstract: Quantitative bias analysis (QBA) permits assessment of the expected impact of various imperfections of the available data on the results and conclusions of a particular real-world study. This article extends QBA methodology to multivariable time-to-event analyses with right-censored endpoints, possibly including time-varying exposures or covariates. The proposed approach employs data-driven simulations, which preserve important features of the data at hand while offering flexibility in controlling the parameters and assumptions that may affect the results. First, the steps required to perform data-driven simulations are described, and then two examples of real-world time-to-event analyses illustrate their implementation and the insights they may offer. The first example focuses on the omission of an important time-invariant predictor of the outcome in a prognostic study of cancer mortality, and permits separating the expected impact of confounding bias from noncollapsibility. The second example assesses how imprecise timing of an interval-censored event—ascertained only at sparse times of clinic visits—affects its estimated association with a time-varying drug exposure. The simulation results also provide a basis for comparing the performance of two alternative strategies for imputing the unknown event times in this setting. The R scripts that permit the reproduction of our examples are provided

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
American journal of epidemiology. - 194, 1 (2025) , 233-242, ISSN: 1476-6256

Event
Veröffentlichung
(where)
Freiburg
(who)
Universität
(when)
2024
Creator
Abrahamowicz, Michal
Beauchamp, Marie-Eve
Boulesteix, Anne-Laure
Morris, Tim P
Sauerbrei, Wilhelm F.
Kaufman, Jay S.

DOI
10.1093/aje/kwae058
URN
urn:nbn:de:bsz:25-freidok-2488048
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:25 AM CEST

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Time of origin

  • 2024

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