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      Introducing the new CONSORT extension for stepped-wedge cluster randomised trials

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      Author(s): 1 , , 2 , 3 , 2 , 4
      Publication date (Electronic):
      Journal: Trials
      Publisher: BioMed Central

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          Abstract

          The use of the stepped-wedge cluster randomised trial (SW-CRT) is on the increase, and although there are still relatively few SW-CRTs currently published its use is bound to show an increase in the near future. An extension of the CONSORT reporting guideline for SW-CRTs has recently been developed. By making reporting guidelines for this innovative design available relatively early in its development, it is possible that the methodological conduct and reporting of future SW-CRTs will not be at the same risk of low-quality of reporting as is the case with many other study designs. We provide a brief overview of this reporting guideline and encourage authors to use it appropriately; and for journal editors to endorse its use.

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          Statistical efficiency and optimal design for stepped cluster studies under linear mixed effects models

          Alan Girling, Karla Hemming (2016)
          In stepped cluster designs the intervention is introduced into some (or all) clusters at different times and persists until the end of the study. Instances include traditional parallel cluster designs and the more recent stepped‐wedge designs. We consider the precision offered by such designs under mixed‐effects models with fixed time and random subject and cluster effects (including interactions with time), and explore the optimal choice of uptake times. The results apply both to cross‐sectional studies where new subjects are observed at each time‐point, and longitudinal studies with repeat observations on the same subjects. The efficiency of the design is expressed in terms of a ‘cluster‐mean correlation’ which carries information about the dependency‐structure of the data, and two design coefficients which reflect the pattern of uptake‐times. In cross‐sectional studies the cluster‐mean correlation combines information about the cluster‐size and the intra‐cluster correlation coefficient. A formula is given for the ‘design effect’ in both cross‐sectional and longitudinal studies. An algorithm for optimising the choice of uptake times is described and specific results obtained for the best balanced stepped designs. In large studies we show that the best design is a hybrid mixture of parallel and stepped‐wedge components, with the proportion of stepped wedge clusters equal to the cluster‐mean correlation. The impact of prior uncertainty in the cluster‐mean correlation is considered by simulation. Some specific hybrid designs are proposed for consideration when the cluster‐mean correlation cannot be reliably estimated, using a minimax principle to ensure acceptable performance across the whole range of unknown values. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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            Stepped wedge cluster randomized controlled trial designs: a review of reporting quality and design features

            Michael J. Grayling, James M S Wason, Adrian P Mander (2017)
            Background The stepped wedge (SW) cluster randomized controlled trial (CRCT) design is being used with increasing frequency. However, there is limited published research on the quality of reporting of SW-CRCTs. We address this issue by conducting a literature review. Methods Medline, Ovid, Web of Knowledge, the Cochrane Library, PsycINFO, the ISRCTN registry, and ClinicalTrials.gov were searched to identify investigations employing the SW-CRCT design up to February 2015. For each included completed study, information was extracted on a selection of criteria, based on the CONSORT extension to CRCTs, to assess the quality of reporting. Results A total of 123 studies were included in our review, of which 39 were completed trial reports. The standard of reporting of SW-CRCTs varied in quality. The percentage of trials reporting each criterion varied to as low as 15.4%, with a median of 66.7%. Conclusions There is much room for improvement in the quality of reporting of SW-CRCTs. This is consistent with recent findings for CRCTs. A CONSORT extension for SW-CRCTs is warranted to standardize the reporting of SW-CRCTs. Electronic supplementary material The online version of this article (doi:10.1186/s13063-017-1783-0) contains supplementary material, which is available to authorized users.
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              Timeline cluster: a graphical tool to identify risk of bias in cluster randomised trials

              Agnès Caille, Sally Kerry, Elsa Tavernier … (2016)
              Article 0 comments Cited 29 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Karla Hemming: k.hemming@bham.ac.uk , K.hemming@bham.ac.uk
                Monica Taljaard: mtaljaard@ohri.ca
                Jeremy Grimshaw: jgrimshaw@ohri.ca
                Journal
                Journal ID (nlm-ta): Trials
                Journal ID (iso-abbrev): Trials
                Title: Trials
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1745-6215
                Publication date (Electronic): 18 January 2019
                Publication date PMC-release: 18 January 2019
                Publication date Collection: 2019
                Volume: 20
                Electronic Location Identifier: 68
                Affiliations
                [1 ]ISNI 0000 0004 1936 7486, GRID grid.6572.6, Institute of Applied Health Research, , University of Birmingham, ; Birmingham, B15 2TT UK
                [2 ]ISNI 0000 0000 9606 5108, GRID grid.412687.e, Clinical Epidemiology Program, Ottawa Hospital Research Institute, ; 1053 Carling Avenue, Ottawa, ON K1Y4E9 Canada
                [3 ]ISNI 0000 0001 2182 2255, GRID grid.28046.38, School of Epidemiology and Public Health, , University of Ottawa, ; Ottawa, ON Canada
                [4 ]ISNI 0000 0001 2182 2255, GRID grid.28046.38, Department of Medicine, , University of Ottawa, ; Ottawa, ON Canada
                Article
                Publisher ID: 3116
                DOI: 10.1186/s13063-018-3116-3
                PMC ID: 6339370
                PubMed ID: 30658677
                SO-VID: 2af02638-c9b9-44c5-b674-004c5e0f7882
                Copyright © © The Author(s). 2019
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 18 July 2018
                Date accepted : 7 December 2018
                Categories
                Subject: Commentary
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                issue-copyright-statement © The Author(s) 2019

                ScienceOpen disciplines: Medicine
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                ScienceOpen disciplines: Medicine

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