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What is the immortal time bias?
Such studies may be subject to immortal time bias, meaning that, during the period of observation, there is some interval during which the outcome event cannot occur. The research participants are “immortal” in that they must survive long enough to receive the intervention being studied.
How do you solve immortal time bias?
Immortal time bias can be avoided by acknowledging a change in exposure status using a time-dependent covariate. For example, a MDC clinic patient would be considered unexposed from the date of study entry until he or she visits the MDC clinic and exposed from that point forward.
What is guarantee time bias?
The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up.
Is confounding a bias?
Confounding is also a form a bias. Confounding is a bias because it can result in a distortion in the measure of association between an exposure and health outcome.
What is landmark analysis?
In the survival analysis setting, landmark analysis refers to the practice of designating a time point occurring during the follow-up period (known as the landmark time) and analyzing only those subjects who have survived until the landmark time.
Is there such a thing as survival bias?
Your description does not give any details suggesting survival bias is an issue here. Censoring leads to a different type of bias, censoring bias, when not properly accounted for. Your analytic plan of using a Cox model does properly account for censoring thus eliminating censoring bias.
How does censoring bias affect a survival analysis?
Survival bias in survival analysis. Censoring leads to a different type of bias, censoring bias, when not properly accounted for. Your analytic plan of using a Cox model does properly account for censoring thus eliminating censoring bias. Despite that, censoring does reduce the power of an analysis.
When is immortal time bias introduced in a study?
Bias is introduced when this period of ‘immortality’ is misclassified or excluded during analysis, resulting in a distortion of observed effects in favour of the treatment (or exposure) under study by conferring a spurious survival advantage to the treated (or exposed) group (Figure 1). Figure 1. The structure of immortal time bias
Is there a bias in the naive analysis?
In a misguided attempt to correct for non-existing non-adherence, 3 the naive analysis introduces bias. By contrast, the valid analysis accepts that dead people necessarily stop receiving treatment, regardless of the treatment duration they were assigned to. We now need to transfer these insights to the analysis of observational data.