title: Use of the landmark method to address immortal person-time bias in comparative effectiveness research: a simulation study.
abstract: Observational comparative effectiveness and safety studies are often subject to immortal person-time, a period of follow-up during which outcomes cannot occur because of the treatment definition. Common approaches, like excluding immortal time from the analysis or naïvely including immortal time in the analysis, are known to result in biased estimates of treatment effect. Other approaches, such as the Mantel-Byar and landmark methods, have been proposed to handle immortal time. Little is known about the performance of the landmark method in different scenarios. We conducted extensive Monte Carlo simulations to assess the performance of the landmark method compared with other methods in settings that reflect realistic scenarios. We considered four landmark times for the landmark method. We found that the Mantel-Byar method provided unbiased estimates in all scenarios, whereas the exclusion and naïve methods resulted in substantial bias when the hazard of the event was constant or decreased over time. The landmark method performed well in correcting immortal person-time bias in all scenarios when the treatment effect was small, and provided unbiased estimates when there was no treatment effect. The bias associated with the landmark method tended to be small when the treatment rate was higher in the early follow-up period than it was later. These findings were confirmed in a case study of chronic obstructive pulmonary disease. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, U.S.A.. xiaojuan.mi@duke.edu.
authors.forename: Xiaojuan
authors.initials: X
authors.lastname: Mi
authors.affiliation: Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, U.S.A.|Department of Medicine, Duke University School of Medicine, Durham, NC, U.S.A.
authors.forename: Bradley G
authors.initials: BG
authors.lastname: Hammill
authors.affiliation: Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, U.S.A.|Department of Medicine, Duke University School of Medicine, Durham, NC, U.S.A.
authors.forename: Lesley H
authors.initials: LH
authors.lastname: Curtis
authors.affiliation: Institute of Clinical Pharmacy and Pharmaceutical Sciences, National Cheng Kung University, Tainan, Taiwan.
authors.forename: Edward Chia-Cheng
authors.initials: EC
authors.lastname: Lai
authors.affiliation: Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, U.S.A.|Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A.
authors.forename: Soko
authors.initials: S
authors.lastname: Setoguchi
mesh_terms: D015982:Bias; D057186:Comparative Effectiveness Research; D006801:Humans; D009010:Monte Carlo Method; D029424:Pulmonary Disease, Chronic Obstructive; D013997:Time Factors; D016896:Treatment Outcome
keywords: Monte Carlo simulations; immortal time bias; landmark methods; observational study; survival analysis; time-varying treatment