What should be done and what should be avoided when comparing two treatments?

Florie Brion Bouvier; Raphaël Porcher

doi:10.1016/j.beha.2023.101473

What should be done and what should be avoided when comparing two treatments?

Best Pract Res Clin Haematol. 2023 Jun;36(2):101473. doi: 10.1016/j.beha.2023.101473. Epub 2023 May 6.

Authors

Florie Brion Bouvier¹, Raphaël Porcher²

Affiliations

¹ Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France.
² Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France; Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France. Electronic address: raphael.porcher@aphp.fr.

PMID: 37353297
DOI: 10.1016/j.beha.2023.101473

Abstract

The preferred approach to compare two treatments is a randomized controlled trial (RCT). Indeed, randomization ensures that the groups compared are similar. Well-designed and well-conducted RCTs thus allow to draw causal conclusions on the relative efficacy and safety of treatments compared. However, it is not always possible to conduct RCTs for all clinical questions of interest, and observational data may also be used to infer on the relative effectiveness of treatments. In this review, we present different approaches that allow statistically valid comparisons of the effectiveness of treatments using observational data under some assumptions. Those are based on regression modelling or the propensity score. We also present the principles of target trial emulation.

Keywords: Causality; Clinical trials; Confounding; Observational studies; Statistics.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Humans
Randomized Controlled Trials as Topic*