Impact of "time zero" of Follow-Up Settings in a Comparative Effectiveness Study Using Real-World Data with a Non-user Comparator: Comparison of Six Different Settings

Abstract

Background Time-related bias can lead to misleading conclusions. Properly setting the "time zero" of follow-up is crucial for avoiding these biases. However, the time-zero setting is challenging when comparing users and non-users of a study drug because the latter do not have a time point for starting treatment. Objective This methodological study aimed to illustrate the impact of different time-zero settings on effect estimates in a comparative effectiveness study using real-world data with a non-user comparator. Methods Data for type 2 diabetes patients were extracted from an administrative claims database, and the onset of diabetic retinopathy (study outcome) was compared between users (treatment group) and non-users (non-use group) of lipid-lowering agents. We applied six time-zero settings to the same dataset. The adjusted hazard ratio (HR) for the outcome was estimated using a Cox regression model in each time-zero setting, and the obtained results were compared among the settings. Results Of the six settings, three (study entry date [SED] vs SED [naïve approach], treatment initiation [TI] vs SED, TI vs Matched [random order]) showed that the treatment had a reduced risk of the outcome (HR [95%

Strategies to Address Current Challenges in Real-World Evidence Generation in Japan

“…On the other hand, setting “time zero” either before eligibility and treatment assignment or at eligibility and before treatment assignment introduces immortal time bias [ 14 ]. A recently published study using a Japanese database showed that, in the new user versus non-user design, different settings of “time zero” for non-users (i.e., at eligibility assignment, by propensity score matching, by random selection, and the cloning method) would generate substantially different results in the parameters evaluated [ 15 ]. In RWD studies comparing a treatment with an active comparator, the new user active comparator design can accommodate for this misalignment by anchoring “time zero” of follow-up to treatment initiation and eligibility [ 40 ].…”

“…Additionally, time-related bias is generally under-considered with respect to confounding bias. Time-related bias is potentially more important than randomization itself in the context of target trial emulation [ 14 ]; it is harder to address due to the needs of data at multiple time points, and is highly dependent on the study design [ 15 ].…”

External comparators and estimands

“…Moreover, there are cases where no treatment is available at all (Wakabayashi et al, 2023), such that it is simply not possible to define baseline by means of any treatment start date.…”

Misleading and avoidable: design-induced biases in observational studies evaluating cancer screening -- the example of site-specific effectiveness of screening colonoscopy

“…For the two designs without alignment we used a cohort study design, where the assignment to study arms occurs before time zero (pre-baseline), and a nested case control study design, where the assignment to study arms occurs after time zero (post-baseline). The current paper is part of a growing literature identifying violations of alignment at time zero as a potential source of major bias in observational studies [6, 7, 8].…”