Abstract
BACKGROUND: A key aspect of the design of randomised controlled trials (RCTs) is determining the sample size. It is important that the trial sample size is appropriately calculated. The required sample size will differ by clinical area, for instance, due to the prevalence of the condition and the choice of primary outcome. Additionally, it will depend upon the choice of target difference assumed in the calculation. Focussing upon the hip and knee osteoarthritis population, this study aims to systematically review how the trial size was determined for trials of osteoarthritis, on what basis, and how well these aspects are reported. METHODS: Several electronic databases (Medline, Cochrane library, CINAHL, EMBASE, PsycINFO, PEDro and AMED) will be searched to identify articles on RCTs of hip and knee osteoarthritis published in 2016. Articles will be screened for eligibility and data extracted independently by two reviewers. Data will be extracted on study characteristics (design, population, intervention and control treatments), primary outcome, chosen sample size and justification, parameters used to calculate the sample size (including treatment effect in control arm, level of variability in primary outcome, loss to follow-up rates). Data will be summarised across the studies using appropriate summary statistics (e.g. n and %, median and interquartile range). The proportion of studies which report each key component of the sample size calculation will be presented. The reproducibility of the sample size calculation will be tested. DISCUSSION: The findings of this systematic review will summarise the current practice for sample size calculation in trials of hip and knee osteoarthritis. It will also provide evidence on the completeness of the reporting of the sample size calculation, reproducibility of the chosen sample size and the basis for the values used in the calculation. TRIAL REGISTRATION: As this review was not eligible to be registered on PROSPERO, the summary information was uploaded to Figshare to make it publicly accessible in order to avoid unnecessary duplication amongst other benefits ( https://doi.org/10.6084/m9.figshare.5009027.v1) ; Registered January 17, 2017.