ArticleJournal of epidemiology2026
Evaluation of Time-related Bias With Non-user Control.
Article in Journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn observational studies estimating the association between treatment and time-to-event outcomes, time-related biases can substantially impact results. Immortal time bias is one of such biases, and two types are known: misclassified immortal time bias and excluded immortal time bias. These biases often arise from incorrect time-zero definition, especially with non-user controls. This study aims to illustrate immortal time bias in non-user controls using formulas, simulations, and real-world data.
methodsFor our simulations, we considered two scenarios: one with no confounding and no treatment effect, and the other with time-dependent confounding. We compare three different settings of time-zero for treatment and control groups. Method 1: Both groups were followed from cohort entry date (CED). Method 2: The treatment group was followed from treatment initiation date (TID), while the non-user group was followed from CED. Method 3: The treatment group was followed from TID, and non-users were matched to treatment patients, followed from the corresponding TID of their matched patient.
resultsOur simulation showed that both method 1 and method 2 can exhibit large biases in the estimated treatment effect due to immortal time bias. The magnitude of the bias is greater for method 1 than for method 2. On the other hand, method 3 showed almost no bias. Even in the presence of time-dependent confounding, method 3 did not introduce bias.
conclusionTo reduce time-related biases, it is crucial for researchers to carefully define an appropriate time-zero, especially when using a non-user control group.
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