Supplementary material: Dependent censoring bias assessment using inverse probability of censoring weights: Type 2 diabetes mellitus risk in patients initiating bisoprolol versus other antihypertensives in a Clinical Practice Research Datalink cohort study
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posted on 2024-10-17, 10:25 authored by Antoine Pinon, Arthur Allignol, Thilo Hohenberger, Caroline Foch, Emmanuelle Boutmy, Ulrike HostalekThese are peer-reviewed supplementary materials for the article 'Dependent censoring bias assessment using inverse probability of censoring weights: Type 2 diabetes mellitus risk in patients initiating bisoprolol versus other antihypertensives in a Clinical Practice Research Datalink cohort study' published in the Journal of Comparative Effectiveness Research.
A.1: Censoring modeling
- A.1.1: Prior knowledge
- A.1.2: Univariate Cox model for T2DM
- A.1.2.1: Multivariate Cox model for censoring
- Table: A1
- A.2: Weights distribution
- A.3: Dependant censoring evaluation: IPCW Kaplan Meier curves A–E
- A.4: IPCW Cox models
- A ‒ calcium-channel blockers
- B – Diuretics vs bisoprolol
- C – Other beta blockers vs bisoprolol
- A.5: competing risks analysis results
- A ‒ Cause-specific hazard ratios for T2DM
- B ‒ Subdistribution hazard ratios for T2DM
- C ‒ Cause-specific hazard ratios for DFM
- D ‒ Subdistribution hazard ratios for DFM
