Presence Of Immortal Time Bias Research Articles

Distorting Effect of Immortal Time Bias on the Association Between Catheter Ablation for Atrial Fibrillation and Incident Stroke: Caveat Emptor

We assessed the presence of immortal time bias (ITB) in observational studies evaluating the effectiveness of radiofrequency catheter ablation for atrial fibrillation (AF) on reduction of stroke. Eligible studies were classified based on presence or absence of ITB. Hazard ratios (HRs) were pooled using the random-effects model. Eight of 10 (80%) studies were subject to ITB. Pooling studies without ITB indicated no statistically significant reduction in incident strokes (HR 0.75; 95% confidence interval [CI], 0.49-1.02]. In conclusion, the pervasiveness of ITB in observational studies precludes definitive conclusions regarding an effect of AF ablation on strokes. Further studies designed to avoid ITB are warranted.

Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data.

Acquiring real-world evidence is crucial to support health policy, but observational studies are prone to serious biases. An approach was recently proposed to overcome confounding and immortal-time biases within the emulated trial framework. This tutorial provides a step-by-step description of the design and analysis of emulated trials, as well as R and Stata code, to facilitate its use in practice. The steps consist in: (i) specifying the target trial and inclusion criteria; (ii) cloning patients; (iii) defining censoring and survival times; (iv) estimating the weights to account for informative censoring introduced by design; and (v) analysing these data. These steps are illustrated with observational data to assess the benefit of surgery among 70–89-year-old patients diagnosed with early-stage lung cancer. Because of the severe unbalance of the patient characteristics between treatment arms (surgery yes/no), a naïve Kaplan-Meier survival analysis of the initial cohort severely overestimated the benefit of surgery on 1-year survival (22% difference), as did a survival analysis of the cloned dataset when informative censoring was ignored (17% difference). By contrast, the estimated weights adequately removed the covariate imbalance. The weighted analysis still showed evidence of a benefit, though smaller (11% difference), of surgery among older lung cancer patients on 1-year survival. Complementing the CERBOT tool, this tutorial explains how to proceed to conduct emulated trials using observational data in the presence of immortal-time bias. The strength of this approach is its transparency and its principles that are easily understandable by non-specialists.