Understanding and identifying immortal-time bias in surgical health services research: An example using surgical resection of stage IV breast cancer.

ABSTRACT

Surgical health services researchers are increasingly utilizing observational data to assess associations between treatments and outcomes, especially since some procedures are unable to be evaluated through randomized controlled trials. However, the results of many of these studies may be affected by the presence of immortal-time bias, which exists when treatment does not occur on Day 0 of the study. This bias can result in researchers overestimating a treatment benefit, or even observe a treatment benefit when none exists. In this paper, we describe what immortal-time bias is, the challenges it presents, and how to recognize and address it using the real-world example of surgical resection of the primary tumor for stage IV breast cancer throughout. In our example, we guide researchers and illustrate how the early studies, which did not account for immortal-time bias, suggested a protective benefit of surgery, and how these results were supplanted by more recent studies through identifying and addressing immortal-time bias in their design and analyses.