Frameworks and methods for estimating the causal effect of clinical treatment in orthopaedics: a scoping review

The gold standard for establishing the causal effect of a clinical treatment is a randomized controlled trial, which is challenging to apply in orthopaedics, mainly due to ethical reasons. Therefore, retrospective observational studies were conducted to elucidate potential treatment effects. However, clinicians rarely receive guidance on how to apply modern causal inference methods to strengthen conclusions drawn from such data and support evidence-based decision-making. The objective of this scoping review was to facilitate a better understanding of the use of causal inference methods in orthopaedics. The scoping review adheres to the Joanna Briggs Institute methodology and the five-stage framework of Arksey and O'Malley. Two themes, 'orthopaedic interventions' and 'causal inference', guided the search strategy development for this scoping review. A literature search of observational studies was conducted using the PubMed, Cochrane Central Register of Controlled Trials, EMBASE, and SCOPUS databases. Studies describing the use of causal inference frameworks in clinical treatment in orthopaedics were included. Of 6,244 records, 85 studies were included in the study. Propensity score matching and inverse probability of treatment weighting were the most common methods. Multicentric studies predominated, while the use of formal causal inference frameworks, such as target trial emulation and directed acyclic graphs, was rare. Causal inference is increasingly used in orthopaedics, although formal frameworks, such as target trial emulation and causal diagrams, remain underutilized. We recommend using prospective, publicly available protocols that incorporate these tools to enhance transparency and validity.