Immortal time bias

 To produce valid results, both observational studies and randomised trials depend on correct classifications of exposure (or treatment) and follow-up. Immortal time bias is a time-related misclassification that can seriously bias the outcome of an investigation. The phenomenon occurs when either the exposed group is assigned a follow-up period that could not have included the events under study (like time on a treatment waiting list). Or when exposed subjects with early events are excluded from the evaluation, ensuring corresponding survival among the remaining.

For example, it was reported (1) from a randomised trial of the effect of a radiation sensitiser on the survival of inoperable lung cancer patients, that the subgroup of patients (36%) who completed the course of radiation therapy augmented by the sensitiser survived a median of 22 months, twice as long as the patients in the control group. However, the median survival for the entire treatment group was only 13 months, not much different from to the median survival of 11 months in the control group.

The example shows the importance of not excluding randomised patients from the analysis of a trial designed to show superiority of a treatment. As observational studies do not include randomisation, they require careful consideration regarding inclusion/exclusion criteria, follow-up, and handling of missing data. Without a carefully developed analysis strategy, significance testing of data alone can easily mislead the investigator.

References

1. Strickland D. OXiGENE's Sensamide Data May Support Neu-Sensamide. BioWorld 1997, September 17. https://www.bioworld.com/articles/484928

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