In comparative effectiveness research, treated and control patients might have a different start of follow-up as treatment is often started later in the disease trajectory. This typically occurs when data from treated and controls are not collected within the same source. Only patients who did not yet experience the event of interest whilst in the control condition end up in the treatment data source. In case of unobserved heterogeneity, these treated patients will have a lower average risk than the controls. We illustrate how failing to account for this time-lag between treated and controls leads to bias in the estimated treatment effect. We define estimands and time axes, then explore five methods to adjust for this time-lag bias by utilising the time between diagnosis and treatment initiation in different ways. We conducted a simulation study to evaluate whether these methods reduce the bias and then applied the methods to a comparison between fertility patients treated with insemination and similar but untreated patients. We conclude that time-lag bias can be vast and that the time between diagnosis and treatment initiation should be taken into account in the analysis to respect the chronology of the disease and treatment trajectory.

翻译：在比较效果研究中，治疗组与对照组患者可能具有不同的随访起始时间，因为治疗通常在疾病轨迹后期开始。当治疗组和对照组的数据并非来自同一数据源时，这种情况尤为常见——仅那些在对照组条件下未发生目标事件的患者才会进入治疗数据源。当存在未观测异质性时，这些治疗组患者的平均风险将低于对照组。我们阐明了未能校正治疗组与对照组间时间滞后会导致治疗效果估计偏倚。首先定义目标估计量和时间轴，随后通过不同方式利用诊断至治疗启动的时间间隔，探索五种校正该偏倚的方法。通过模拟研究评估这些方法的偏倚校正效果，并将方法应用于接受人工授精治疗的不孕患者与未接受治疗的相似患者的比较。结论指出：时间滞后偏倚可能极为显著，在分析中必须将诊断至治疗启动的时间间隔纳入考虑，以尊重疾病与治疗轨迹的时间序列。