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Observational studies of treatment effectiveness in neurology.

Tomas KalincikIzanne RoosSifat Sharmin
Published in: Brain : a journal of neurology (2023)
The capacity and power of data from cohorts, registries and randomised trials to provide answers to contemporary clinical questions in neurology has increased considerably over the last two decades. Novel sophisticated statistical methods are enabling us to harness these data to guide treatment decisions, but their complexity is making appraisal of clinical evidence increasingly demanding. In this review, we discuss several methodological aspects of contemporary research of treatment effectiveness in observational data in neurology, aimed at academic neurologists and analysts specialising in outcomes research. The review discusses specifics of the sources of observational data and their key features. It focuses on the limitations of observational data, and study design and statistical approaches aimed to overcome these limitations. Among the examples of leading clinical themes typically studied with analyses of observational data, the review discusses methodological approaches to comparative treatment effectiveness, development of diagnostic criteria and definitions of clinical outcomes. Finally, this review provides a brief summary of key points that will help clinical audience critically evaluate design and analytical aspects of studies of disease outcomes using observational data.
Keyphrases
  • electronic health record
  • big data
  • randomized controlled trial
  • clinical trial
  • machine learning
  • metabolic syndrome
  • skeletal muscle
  • artificial intelligence
  • adipose tissue
  • drinking water
  • weight loss
  • double blind