Background The integration of real-world evidence (RWE) from real-world data (RWD) in
clinical research is crucial for bridging the gap between clinical trial results and real-world …

One of the key challenges in pharmacoepidemiological studies is that of uncontrolled
confounding, which occurs when confounders are poorly measured, unmeasured or …

Abstract Background Direct oral anticoagulants (DOACs) are preferred over warfarin in
patients with atrial fibrillation (AFib). However, their safety and effectiveness in patients with …

Purpose Propensity score weighting is a popular approach for estimating treatment effects
using observational data. Different sets of propensity score‐based weights have been …

Aim: Comparative effectiveness research using real-world data often involves pairwise
propensity score matching to adjust for confounding bias. We show that corresponding …

Decision-analytic models (DAMs) are essentially informative yet complex tools for solving
questions in medical decision making. When their complexity grows, the need for causal …

Objective: The estimand framework offers a structured approach to define the treatment
effect to be estimated in a clinical study. Defining the estimand upfront helps formulating the …

OBJECTIVES It is unknown which confounding adjustment methods are currently used in
the field of cardiothoracic surgery and whether these are appropriately applied. The aim of …

The chapter gives an introduction to basic concepts of causal reasoning and to key methods
for causal inference as developed and used in epidemiology over the last two decades. It …

We congratulate Howard and colleagues1 with their important contribution to current
knowledge on the prognosis of moderate aortic stenosis regarding major adverse …