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Learning from Cochrane systematic reviews: what improvements do these suggest for the design of trials?

Stefania PiroscaMichael ClarkeShaun Treweek
Published in: F1000Research (2020)
Background: Many randomised trials have serious methodological flaws that fatally undermine their results, which makes the research wasteful. This is of concern for many, including those doing systematic reviews that include trials. Cochrane systematic reviews have a section called '  Implications for research', which allows authors of the review to present their conclusions on how future research might be improved. Looking at these conclusions might highlight priority areas for improvement. Methods: We focused on the Cochrane Schizophrenia Review Group and the Multiple sclerosis and rare diseases of the central nervous system Review Group (the MS Review Group).  Reviews with citation dates between 2009 and 2019 were identified and the recommendations of review authors in '  Implications for research' were put into categories. Results: Between 2009 and 2019 we identified 162 reviews for the Schizophrenia Review Group and 43 reviews for the MS Review Group. We created 22 categories of recommendations in total, of which 12 were common to both groups. The five most used categories were the same for both: better choice of outcomes; better choice of intervention/comparator; longer follow-up; larger sample size; use of validated scales.  Better choice of outcomes and/or intervention/comparator was recommended in over 50% of reviews. Longer follow-up and larger sample size were recommended in over a third, with use of validated scales being suggested in around a fifth of reviews. There was no obvious pattern of improvement over time for trials included in systematic reviews published by both groups. Conclusions: We suggest that trialists working in these and other areas ask themselves, or are compelled to do so by others (e.g. funders), why they have chosen their outcomes, intervention and comparator, whether follow-up is long enough, if the sample size is big enough and whether the scales they choose to measure their outcomes are appropriate.
Keyphrases
  • multiple sclerosis
  • systematic review
  • meta analyses
  • randomized controlled trial
  • ms ms
  • type diabetes
  • adipose tissue
  • white matter
  • artificial intelligence
  • big data
  • study protocol