Core Concepts: Self‐Controlled Designs in Pharmacoepidemiology
Sophie H. Bots, Jeremy Brown, Angel Wong, Ivonne Martin, Ian Douglas, Olaf H. Klungel, Anna Schultze
Abstract
One of the key challenges in pharmacoepidemiological studies is that of uncontrolled confounding, which occurs when confounders are poorly measured, unmeasured or unknown. Self-controlled designs can help address this issue, as their key comparison is not between people, but periods of time within the same person. This controls for all time-stable confounders (genetics) and in the absence of time-varying confounding negates the need for an external control group. However, these benefits come at the cost of strong assumptions, not all of which are verifiable. This review briefly introduces the reader to different types of self-controlled study designs, their terminology and highlights key publications through an annotated reference list. We include a practical description of how these designs can be implemented and visualised using recent examples, and finish by discussing recent developments. We hope this review will serve as a starting point for researchers looking to apply self-controlled designs in their own work.