Randomised clinical trials are the primary source of evidence, guiding the use of disease-modifying drugs in multiple sclerosis. However, the spectrum of questions that can be answered in the trial setting is relatively narrow. 'Real-world' observational data analysis has always been the major source of evidence for epidemiology, aetiology, outcomes and prognostics, but is now also increasingly used to study treatment effectiveness. While analyses of observational cohorts typically offer superior power, generalisability and duration of follow-up relative to prospective randomised trials, they are also subject to multiple biases. It is the role of researchers to mitigate bias and to ensure the results of observational studies are robust and valid. In this review of observational data research, we provide an overview of the inherent biases, the available mitigation strategies, and the state and direction of contemporary treatment outcomes research. The review will help clinicians critically appraise published results of observational studies.
- Observational data