Immortal Time Bias in Post-Operative Radiation Studies Utilizing the National Cancer Data Base

Abstract

Studies employing large observational oncology databases, such as the National Cancer Database (NCDB), are appearing with increasing frequency in the oncology literature. Immortal time bias is a well described and often overlooked type of confounding selection bias that may give the illusion of treatment effectiveness in time to event (survival) analyses via marked alterations in effect sizes (i.e. hazard ratios). ‘Immortal time’ may arise during observational study design when follow-up incorporates a period of time where either death or the measured study outcome cannot occur. Bias in immortal time can occur in analyses designed to evaluate the impact of a specific intervention that calculates overall survival (OS) from time of diagnosis (in contrast to time of treatment), and in study designs that do not account for the time to receipt of adjuvant therapies (e.g. postoperative radiation therapy or PORT). Given the increase in NCDB analyses being used to evaluate the impact of PORT, we sought to examine how often-published studies accounted for time dependent confounders. We performed a PUBMED search using the terms: ‘NCDB,’ ‘National Cancer Data Base,’ ‘postoperative radiation,’ and ‘adjuvant radiation therapy,’ published between 2015-2018. Inclusion for review involved all manuscripts where PORT (with or without chemotherapy) was delivered to any disease site as a comparative arm within the study. This led to review of 42 publications. We specifically assessed how OS was defined and whether any statistical metrics were used to account for potential immortal time bias in the receipt of PORT via landmark analyses or adjusted hazard ratios. Of the 42 publications reviewed, OS was not defined in 8 (19%) studies, was determined from date of diagnosis in 20 (47.6%), from date of treatment start date in 8(19%), or from diagnosis with a one month landmark time in 6 (14.2%). There was no landmark analysis, sequential landmark definition, or an adjusted cox model with a clear time dependent definition in 31 studies (73.8%) when accounting for time to PORT. Amongst the 11 studies that did a landmark analysis, 9 of them (81.8%) had a landmark time with rationale that was not clearly defined. Among the manuscripts analyzed, PORT was concluded to be beneficial in 38 studies (90.4%). Immortal time bias may obscure the effect size (usually via overestimating HR) of PORT as an adjuvant therapy and affect the validity of NCDB hypothesis generating studies. The NCDB has many strengths with its power to generate valid research questions, but its inherent biases require rigorous statistical methods to help validate conclusions. Studies assessing PORT are encouraged to measure OS from treatment start date and perform sequential landmark analyses to help quantify PORT effect size and mitigate this common confounder.