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      Practical help for specifying the target difference in sample size calculations for RCTs: the DELTA2 five-stage study, including a workshop

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          Abstract

          Background

          The randomised controlled trial is widely considered to be the gold standard study for comparing the effectiveness of health interventions. Central to its design is a calculation of the number of participants needed (the sample size) for the trial. The sample size is typically calculated by specifying the magnitude of the difference in the primary outcome between the intervention effects for the population of interest. This difference is called the ‘target difference’ and should be appropriate for the principal estimand of interest and determined by the primary aim of the study. The target difference between treatments should be considered realistic and/or important by one or more key stakeholder groups.

          Objective

          The objective of the report is to provide practical help on the choice of target difference used in the sample size calculation for a randomised controlled trial for researchers and funder representatives.

          Methods

          The Difference ELicitation in TriAls 2 (DELTA 2) recommendations and advice were developed through a five-stage process, which included two literature reviews of existing funder guidance and recent methodological literature; a Delphi process to engage with a wider group of stakeholders; a 2-day workshop; and finalising the core document.

          Results

          Advice is provided for definitive trials (Phase III/IV studies). Methods for choosing the target difference are reviewed. To aid those new to the topic, and to encourage better practice, 10 recommendations are made regarding choosing the target difference and undertaking a sample size calculation. Recommended reporting items for trial proposal, protocols and results papers under the conventional approach are also provided. Case studies reflecting different trial designs and covering different conditions are provided. Alternative trial designs and methods for choosing the sample size are also briefly considered.

          Conclusions

          Choosing an appropriate sample size is crucial if a study is to inform clinical practice. The number of patients recruited into the trial needs to be sufficient to answer the objectives; however, the number should not be higher than necessary to avoid unnecessary burden on patients and wasting precious resources. The choice of the target difference is a key part of this process under the conventional approach to sample size calculations. This document provides advice and recommendations to improve practice and reporting regarding this aspect of trial design. Future work could extend the work to address other less common approaches to the sample size calculations, particularly in terms of appropriate reporting items.

          Funding

          Funded by the Medical Research Council (MRC) UK and the National Institute for Health Research as part of the MRC–National Institute for Health Research Methodology Research programme.

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          Most cited references155

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          Measures of knee function: International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form, Knee Injury and Osteoarthritis Outcome Score (KOOS), Knee Injury and Osteoarthritis Outcome Score Physical Function Short Form (KOOS-PS), Knee Outcome Survey Activities of Daily Living Scale (KOS-ADL), Lysholm Knee Scoring Scale, Oxford Knee Score (OKS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Activity Rating Scale (ARS), and Tegner Activity Score (TAS).

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            An audit of sample sizes for pilot and feasibility trials being undertaken in the United Kingdom registered in the United Kingdom Clinical Research Network database

            Background There is little published guidance as to the sample size required for a pilot or feasibility trial despite the fact that a sample size justification is a key element in the design of a trial. A sample size justification should give the minimum number of participants needed in order to meet the objectives of the trial. This paper seeks to describe the target sample sizes set for pilot and feasibility randomised controlled trials, currently running within the United Kingdom. Methods Data were gathered from the United Kingdom Clinical Research Network (UKCRN) database using the search terms ‘pilot’ and ‘feasibility’. From this search 513 studies were assessed for eligibility of which 79 met the inclusion criteria. Where the data summary on the UKCRN Database was incomplete, data were also gathered from: the International Standardised Randomised Controlled Trial Number (ISRCTN) register; the clinicaltrials.gov website and the website of the funders. For 62 of the trials, it was necessary to contact members of the research team by email to ensure completeness. Results Of the 79 trials analysed, 50 (63.3%) were labelled as pilot trials, 25 (31.6%) feasibility and 14 were described as both pilot and feasibility trials. The majority had two arms (n = 68, 86.1%) and the two most common endpoints were continuous (n = 45, 57.0%) and dichotomous (n = 31, 39.2%). Pilot trials were found to have a smaller sample size per arm (median = 30, range = 8 to 114 participants) than feasibility trials (median = 36, range = 10 to 300 participants). By type of endpoint, across feasibility and pilot trials, the median sample size per arm was 36 (range = 10 to 300 participants) for trials with a dichotomous endpoint and 30 (range = 8 to 114 participants) for trials with a continuous endpoint. Publicly funded pilot trials appear to be larger than industry funded pilot trials: median sample sizes of 33 (range = 15 to 114 participants) and 25 (range = 8 to 100 participants) respectively. Conclusion All studies should have a sample size justification. Not all studies however need to have a sample size calculation. For pilot and feasibility trials, while a sample size justification is important, a formal sample size calculation may not be appropriate. The results in this paper describe the observed sample sizes in feasibility and pilot randomised controlled trials on the UKCRN Database.
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              A simple sample size formula for analysis of covariance in randomized clinical trials.

              Randomized clinical trials that compare two treatments on a continuous outcome can be analyzed using analysis of covariance (ANCOVA) or a t-test approach. We present a method for the sample size calculation when ANCOVA is used. We derived an approximate sample size formula. Simulations were used to verify the accuracy of the formula and to improve the approximation for small trials. The sample size calculations are illustrated in a clinical trial in rheumatoid arthritis. If the correlation between the outcome measured at baseline and at follow-up is rho, ANCOVA comparing groups of (1-rho(2))n subjects has the same power as t-test comparing groups of n subjects. When on the same data, ANCOVA is used instead of t-test, the precision of the treatment estimate is increased, and the length of the confidence interval is reduced by a factor 1-rho(2). ANCOVA may considerably reduce the number of patients required for a trial.
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                Author and article information

                Contributors
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                Journal
                Health Technology Assessment
                Health Technol Assess
                National Institute for Health Research
                1366-5278
                2046-4924
                October 2019
                October 2019
                : 23
                : 60
                : 1-88
                Affiliations
                [1 ]Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
                [2 ]Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, UK
                [3 ]Statistical Methodology and Consulting, Novartis Pharma AG, Basel, Switzerland
                [4 ]York Trials Unit, Department of Health Sciences, University of York, York, UK
                [5 ]Johnson & Johnson, Titusville, NJ, USA
                [6 ]Imperial Clinical Trials Unit, Imperial College London, London, UK
                [7 ]Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
                [8 ]Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
                [9 ]Cambridge Centre for Health Services Research, Cambridge Clinical Trials Unit University of Cambridge, Cambridge, UK
                [10 ]Health Economics Group, Norwich Medical School, University of East Anglia, Norwich, UK
                [11 ]Centre for Healthcare Randomised Trials, University of Aberdeen, Aberdeen, UK
                [12 ]Warwick Medical School, Statistics and Epidemiology, University of Warwick, Coventry, UK
                [13 ]Department of Health Sciences, University of York, York, UK
                [14 ]MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK
                [15 ]Health Services Research Unit, University of Aberdeen, Aberdeen, UK
                [16 ]Wessex Institute, University of Southampton, Southampton, UK
                [17 ]School of Population Health and Environmental Sciences, King’s College London, London, UK
                [18 ]Health Economics Group, Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK
                Article
                10.3310/hta23600
                6843113
                31661431
                e9668971-306b-4ea1-be7e-5ab4b388c31b
                © 2019

                Free to read

                http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/non-commercial-government-licence.htm

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