Abstract Number:
3449
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Poster
Participants:
Fang Niu (1), Anna Novelli (2), Mengnan Zhou (2), John Chang (2), John Sim (2), Maria Montez-Rath (3), Michelle C. Odden (4), Vivek Charu (1), Manjula Tamura (3), Jaejin An (2)
Institutions:
(1) N/A, N/A, (2) Kaiser Permanente Southern California, N/A, (3) Stanford University, N/A, (4) Stanford University, School of Medicine, N/A
Co-Author(s):
John Sim
Kaiser Permanente Southern California
Jaejin An
Kaiser Permanente Southern California
First Author:
Presenting Author:
Abstract Text:
Immortal time bias is a significant issue when evaluating treatment effectiveness to inform health policy and decision making in observational studies. It is common in time-to-event drug effectiveness analyses where an index date is not clear. For example, when a treatment is being compared to no treatment or a continuation of treatment. In this case, participants are assigned to groups based on data collected after the cohort entry date. Traditional methods to avoid or minimize such bias include landmark analyses with a predefined follow-up start. More recently, clinical trial emulation analyses with the clone-censor-weight approach were proposed. We performed per-protocol trial emulation analyses with and without clones, and a 3-month landmark analysis, on the mortality risk at 9 months comparing intensification vs continuation of antihypertensive treatment in 65,631 eligible patients with chronic kidney disease and high blood pressure using electronic health records from an integrated health system. We found that the results differ between approaches. The results highlight the importance of selecting the proper methods to address immortal time bias.
Keywords:
Immortal time bias|Emulating Trials|clones|landmark analyses| |
Sponsors:
Section on Statistics in Epidemiology
Tracks:
Pharmacoepidemiology
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