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Albani V, Vale LD, Pearce M, Ostroumova E, Liutsko L. Aspects of economic costs and evaluation of health surveillance systems after a radiation accident with a focus on an ultrasound thyroid screening programme for children. Environ Int 2021; 156:106571. [PMID: 33975128 DOI: 10.1016/j.envint.2021.106571] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 03/31/2021] [Accepted: 04/09/2021] [Indexed: 06/12/2023]
Abstract
Health surveillance initiatives targeted at populations evacuated from, and residing in, areas affected by radiation contamination were implemented by international institutions as well as national and local governments after the nuclear accidents of Chernobyl and Fukushima Dai-ichi nuclear power plants. Most of these initiatives included a component of childhood thyroid cancer monitoring, with the more comprehensive schemes corresponding to national programmes of health monitoring for adults and children around general health and wellbeing. This article provides a short overview of available data on the costs and resources associated with surveillance responses to two recent nuclear accidents: Chernobyl and the Fukushima Dai-Ichi nuclear plant accidents. Moreover, because the balance of costs and benefits of health surveillance after a nuclear accident can influence decisions on implementation, we also present a brief overview of the principles of economic evaluation for collecting and presenting data on costs and outcomes of a surveillance programme after a nuclear accident. We apply these principles in a balance sheet analysis of a post-accident ultrasound thyroid screening programme for children.
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Affiliation(s)
- Viviana Albani
- Health Economics Group, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Luke D Vale
- Health Economics Group, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Mark Pearce
- Health Protection Research Unit for Chemical & Radiation Threats and Hazards, Newcastle University, Newcastle upon Tyne, United Kingdom
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2
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Cook JA, Julious SA, Sones W, Hampson LV, Hewitt C, Berlin JA, Ashby D, Emsley R, Fergusson DA, Walters SJ, Wilson EC, MacLennan G, Stallard N, Rothwell JC, Bland M, Brown L, Ramsay CR, Cook A, Armstrong D, Altman D, Vale LD. Practical help for specifying the target difference in sample size calculations for RCTs: the DELTA 2 five-stage study, including a workshop. Health Technol Assess 2019; 23:1-88. [PMID: 31661431 PMCID: PMC6843113 DOI: 10.3310/hta23600] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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 TriAls2 (DELTA2) 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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Affiliation(s)
- Jonathan A Cook
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Steven A Julious
- Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - William Sones
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Lisa V Hampson
- Statistical Methodology and Consulting, Novartis Pharma AG, Basel, Switzerland
| | - Catherine Hewitt
- York Trials Unit, Department of Health Sciences, University of York, York, UK
| | | | - Deborah Ashby
- Imperial Clinical Trials Unit, Imperial College London, London, UK
| | - Richard Emsley
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Dean A Fergusson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Stephen J Walters
- Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Edward Cf Wilson
- Cambridge Centre for Health Services Research, Cambridge Clinical Trials Unit University of Cambridge, Cambridge, UK
- Health Economics Group, Norwich Medical School, University of East Anglia, Norwich, UK
| | - Graeme MacLennan
- Centre for Healthcare Randomised Trials, University of Aberdeen, Aberdeen, UK
| | - Nigel Stallard
- Warwick Medical School, Statistics and Epidemiology, University of Warwick, Coventry, UK
| | - Joanne C Rothwell
- Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Martin Bland
- Department of Health Sciences, University of York, York, UK
| | - Louise Brown
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Andrew Cook
- Wessex Institute, University of Southampton, Southampton, UK
| | - David Armstrong
- School of Population Health and Environmental Sciences, King's College London, London, UK
| | - Douglas Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Luke D Vale
- Health Economics Group, Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK
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3
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Cook JA, Julious SA, Sones W, Hampson LV, Hewitt C, Berlin JA, Ashby D, Emsley R, Fergusson DA, Walters SJ, Wilson ECF, Maclennan G, Stallard N, Rothwell JC, Bland M, Brown L, Ramsay CR, Cook A, Armstrong D, Altman D, Vale LD. DELTA 2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial. Trials 2018; 19:606. [PMID: 30400926 PMCID: PMC6218987 DOI: 10.1186/s13063-018-2884-0] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 08/29/2018] [Indexed: 12/29/2022] Open
Abstract
Background A key step in the design of a RCT is the estimation of the number of participants needed in the study. The most common approach is to specify a target difference between the treatments for the primary outcome and then calculate the required sample size. The sample size is chosen to ensure that the trial will have a high probability (adequate statistical power) of detecting a target difference between the treatments should one exist. The sample size has many implications for the conduct and interpretation of the study. Despite the critical role that the target difference has in the design of a RCT, the way in which it is determined has received little attention. In this article, we summarise the key considerations and messages from new guidance for researchers and funders on specifying the target difference, and undertaking and reporting a RCT sample size calculation. This article on choosing the target difference for a randomised controlled trial (RCT) and undertaking and reporting the sample size calculation has been dual published in the BMJ and BMC Trials journals Methods The DELTA2 (Difference ELicitation in TriAls) project comprised five major components: systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2); a Delphi study (stage 3); a two-day consensus meeting bringing together researchers, funders and patient representatives (stage 4); and the preparation and dissemination of a guidance document (stage 5). Results and Discussion The key messages from the DELTA2 guidance on determining the target difference and sample size calculation for a randomised caontrolled trial are presented. Recommendations for the subsequent reporting of the sample size calculation are also provided.
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Affiliation(s)
- Jonathan A Cook
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Rd, Oxford, OX3 7LD, UK.
| | - Steven A Julious
- Medical Statistics Group, ScHARR, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - William Sones
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Rd, Oxford, OX3 7LD, UK
| | - Lisa V Hampson
- Statistical Methodology and Consulting, Novartis, Basel, Switzerland.,Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, UK
| | - Catherine Hewitt
- Department of Health Sciences, Seebohm Rowntree Building, University of York, Heslington, York, YO10 5DD, UK
| | - Jesse A Berlin
- Johnson & Johnson, 1125 Trenton-Harbourton Road, Titusville, NJ, 08933, USA
| | - Deborah Ashby
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, Stadium House, 68 Wood Lane, London, W12 7RH, UK
| | - Richard Emsley
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Dean A Fergusson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Stephen J Walters
- Medical Statistics Group, ScHARR, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Edward C F Wilson
- Cambridge Centre for Health Services Research & Cambridge Clinical Trials Unit, University of Cambridge, Institute of Public Health, Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK
| | - Graeme Maclennan
- The Centre for Healthcare Randomised Trials (CHaRT), Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen, AB25 2D, UK
| | - Nigel Stallard
- Warwick Medical School - Statistics and Epidemiology, University of Warwick, Coventry, CV4 7AL, UK
| | - Joanne C Rothwell
- Medical Statistics Group, ScHARR, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Martin Bland
- Department of Health Sciences, Seebohm Rowntree Building, University of York, Heslington, York, YO10 5DD, UK
| | - Louise Brown
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London, WC1V 6LJ, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Health Sciences Building Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Andrew Cook
- Public Health Medicine and Fellow in Health Technology Assessment, Wessex Institute, University of Southampton, Alpha House, Enterprise Road, Southampton, SO16 7NS, UK
| | - David Armstrong
- School of Population Health & Environmental Sciences, Faculty of Life Sciences and Medicine, Kings College London, Addison House, Guy's Campus, London, SE1 1UL, UK
| | - Doug Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Rd, Oxford, OX3 7LD, UK
| | - Luke D Vale
- Health Economics Group, Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK
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Cook JA, Julious SA, Sones W, Hampson LV, Hewitt C, Berlin JA, Ashby D, Emsley R, Fergusson DA, Walters SJ, Wilson ECF, MacLennan G, Stallard N, Rothwell JC, Bland M, Brown L, Ramsay CR, Cook A, Armstrong D, Altman D, Vale LD. DELTA 2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial. BMJ 2018; 363:k3750. [PMID: 30560792 PMCID: PMC6216070 DOI: 10.1136/bmj.k3750] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/09/2018] [Indexed: 11/17/2022]
Affiliation(s)
- Jonathan A Cook
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Oxford OX3 7LD, UK
| | - Steven A Julious
- Medical Statistics Group, ScHARR, University of Sheffield, Sheffield, UK
| | - William Sones
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Oxford OX3 7LD, UK
| | - Lisa V Hampson
- Statistical Methodology and Consulting, Novartis, Basel, Switzerland
- Department of Mathematics and Statistics, Lancaster University, Lancaster, UK
| | - Catherine Hewitt
- Department of Health Sciences, University of York, Heslington, York, UK
| | | | - Deborah Ashby
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, London, UK
| | - Richard Emsley
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Dean A Fergusson
- Clinical Epidemiology Programme, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Stephen J Walters
- Medical Statistics Group, ScHARR, University of Sheffield, Sheffield, UK
| | - Edward C F Wilson
- Cambridge Centre for Health Services Research and Cambridge Clinical Trials Unit, University of Cambridge, Institute of Public Health, Cambridge, UK
| | - Graeme MacLennan
- Centre for Healthcare Randomised Trials (CHaRT), University of Aberdeen, Aberdeen, UK
| | - Nigel Stallard
- Warwick Medical School-Statistics and Epidemiology, University of Warwick, Coventry, UK
| | - Joanne C Rothwell
- Medical Statistics Group, ScHARR, University of Sheffield, Sheffield, UK
| | - Martin Bland
- Department of Health Sciences, University of York, Heslington, York, UK
| | - Louise Brown
- MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, London, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Andrew Cook
- Wessex Institute, University of Southampton, Southampton, UK
| | - David Armstrong
- School of Population Health and Environmental Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Doug Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Oxford OX3 7LD, UK
| | - Luke D Vale
- Health Economics Group, Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
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5
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Cook JA, Julious SA, Sones W, Hampson LV, Hewitt C, Berlin JA, Ashby D, Emsley R, Fergusson DA, Walters SJ, Wilson ECF, Maclennan G, Stallard N, Rothwell JC, Bland M, Brown L, Ramsay CR, Cook A, Armstrong D, Altman D, Vale LD. DELTA 2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial. Trials 2018. [PMID: 30400926 DOI: 10.1186/s13063‐018‐2884‐0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A key step in the design of a RCT is the estimation of the number of participants needed in the study. The most common approach is to specify a target difference between the treatments for the primary outcome and then calculate the required sample size. The sample size is chosen to ensure that the trial will have a high probability (adequate statistical power) of detecting a target difference between the treatments should one exist. The sample size has many implications for the conduct and interpretation of the study. Despite the critical role that the target difference has in the design of a RCT, the way in which it is determined has received little attention. In this article, we summarise the key considerations and messages from new guidance for researchers and funders on specifying the target difference, and undertaking and reporting a RCT sample size calculation. This article on choosing the target difference for a randomised controlled trial (RCT) and undertaking and reporting the sample size calculation has been dual published in the BMJ and BMC Trials journals METHODS: The DELTA2 (Difference ELicitation in TriAls) project comprised five major components: systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2); a Delphi study (stage 3); a two-day consensus meeting bringing together researchers, funders and patient representatives (stage 4); and the preparation and dissemination of a guidance document (stage 5). RESULTS AND DISCUSSION The key messages from the DELTA2 guidance on determining the target difference and sample size calculation for a randomised caontrolled trial are presented. Recommendations for the subsequent reporting of the sample size calculation are also provided.
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Affiliation(s)
- Jonathan A Cook
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Rd, Oxford, OX3 7LD, UK.
| | - Steven A Julious
- Medical Statistics Group, ScHARR, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - William Sones
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Rd, Oxford, OX3 7LD, UK
| | - Lisa V Hampson
- Statistical Methodology and Consulting, Novartis, Basel, Switzerland.,Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, UK
| | - Catherine Hewitt
- Department of Health Sciences, Seebohm Rowntree Building, University of York, Heslington, York, YO10 5DD, UK
| | - Jesse A Berlin
- Johnson & Johnson, 1125 Trenton-Harbourton Road, Titusville, NJ, 08933, USA
| | - Deborah Ashby
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, Stadium House, 68 Wood Lane, London, W12 7RH, UK
| | - Richard Emsley
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Dean A Fergusson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Stephen J Walters
- Medical Statistics Group, ScHARR, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Edward C F Wilson
- Cambridge Centre for Health Services Research & Cambridge Clinical Trials Unit, University of Cambridge, Institute of Public Health, Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK
| | - Graeme Maclennan
- The Centre for Healthcare Randomised Trials (CHaRT), Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen, AB25 2D, UK
| | - Nigel Stallard
- Warwick Medical School - Statistics and Epidemiology, University of Warwick, Coventry, CV4 7AL, UK
| | - Joanne C Rothwell
- Medical Statistics Group, ScHARR, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Martin Bland
- Department of Health Sciences, Seebohm Rowntree Building, University of York, Heslington, York, YO10 5DD, UK
| | - Louise Brown
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London, WC1V 6LJ, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Health Sciences Building Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Andrew Cook
- Public Health Medicine and Fellow in Health Technology Assessment, Wessex Institute, University of Southampton, Alpha House, Enterprise Road, Southampton, SO16 7NS, UK
| | - David Armstrong
- School of Population Health & Environmental Sciences, Faculty of Life Sciences and Medicine, Kings College London, Addison House, Guy's Campus, London, SE1 1UL, UK
| | - Doug Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Rd, Oxford, OX3 7LD, UK
| | - Luke D Vale
- Health Economics Group, Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK
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Cook JA, Julious SA, Sones W, Rothwell JC, Ramsay CR, Hampson LV, Emsley R, Walters SJ, Hewitt C, Bland M, Fergusson DA, Berlin JA, Altman D, Vale LD. Choosing the target difference ('effect size') for a randomised controlled trial - DELTA 2 guidance protocol. Trials 2017; 18:271. [PMID: 28606102 PMCID: PMC5469157 DOI: 10.1186/s13063-017-1969-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 05/04/2017] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND A key step in the design of a randomised controlled trial (RCT) is the estimation of the number of participants needed. By far the most common approach is to specify a target difference and then estimate the corresponding sample size; this sample size is chosen to provide reassurance that the trial will have high statistical power to detect such a difference between the randomised groups (at the planned statistical significance level). The sample size has many implications for the conduct of the study, as well as carrying scientific and ethical aspects to its choice. Despite the critical role of the target difference for the primary outcome in the design of an RCT, the manner in which it is determined has received little attention. This article reports the protocol of the Difference ELicitation in TriAls (DELTA2) project, which will produce guidance on the specification and reporting of the target difference for the primary outcome in a sample size calculation for RCTs. METHODS/DESIGN The DELTA2 project has five components: systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2); a Delphi study (stage 3); a 2-day consensus meeting bringing together researchers, funders and patient representatives, as well as one-off engagement sessions at relevant stakeholder meetings (stage 4); and the preparation and dissemination of a guidance document (stage 5). DISCUSSION Specification of the target difference for the primary outcome is a key component of the design of an RCT. There is a need for better guidance for researchers and funders regarding specification and reporting of this aspect of trial design. The aim of this project is to produce consensus based guidance for researchers and funders.
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Affiliation(s)
- Jonathan A. Cook
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Nuffield Orthopaedic Centre, Windmill Road, Oxford, OX3 7LD UK
| | - Steven A. Julious
- Medical Statistics Group, School of Health and Related Research (ScHARR), The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA UK
| | - William Sones
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Nuffield Orthopaedic Centre, Windmill Road, Oxford, OX3 7LD UK
| | - Joanne C. Rothwell
- Medical Statistics Group, School of Health and Related Research (ScHARR), The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA UK
| | - Craig R. Ramsay
- Health Services Research Unit, University of Aberdeen, Health Sciences Building, Foresterhill, Aberdeen, AB25 2ZD UK
| | - Lisa V. Hampson
- Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF UK
- Statistical Innovation Group, Advanced Analytics Centre, AstraZeneca, Riverside Building, Granta Park, Cambridge, CB21 6GH UK
| | - Richard Emsley
- Centre for Biostatistics, School of Health Sciences, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL UK
| | - Stephen J. Walters
- Medical Statistics Group, School of Health and Related Research (ScHARR), The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA UK
| | - Catherine Hewitt
- Department of Health Sciences, University of York, Heslington, Seebohm Rowntree Building, York, YO10 5DD UK
| | - Martin Bland
- Department of Health Sciences, University of York, Heslington, Seebohm Rowntree Building, York, YO10 5DD UK
| | - Dean A. Fergusson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa Hospital, 501 Smyth Road, Ottawa, ON K1H 8L6 Canada
| | - Jesse A. Berlin
- Johnson & Johnson, 1125 Trenton-Harbourton Road, MS TE3-15, PO Box 200, Titusville, NJ 08560 USA
| | - Doug Altman
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Nuffield Orthopaedic Centre, Windmill Road, Oxford, OX3 7LD UK
| | - Luke D. Vale
- Institute of Health and Society, Newcastle University, The Baddiley-Clark Building, Richardson Road, Newcastle upon Tyne, NE2 4AX UK
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Cook JA, Hislop J, Altman DG, Fayers P, Briggs AH, Ramsay CR, Norrie JD, Harvey IM, Buckley B, Fergusson D, Ford I, Vale LD. Specifying the target difference in the primary outcome for a randomised controlled trial: guidance for researchers. Trials 2015; 16:12. [PMID: 25928502 PMCID: PMC4302137 DOI: 10.1186/s13063-014-0526-8] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Accepted: 12/19/2014] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Central to the design of a randomised controlled trial is the calculation of the number of participants needed. This is typically achieved by specifying a target difference and calculating the corresponding sample size, which provides reassurance that the trial will have the required statistical power (at the planned statistical significance level) to identify whether a difference of a particular magnitude exists. Beyond pure statistical or scientific concerns, it is ethically imperative that an appropriate number of participants should be recruited. Despite the critical role of the target difference for the primary outcome in the design of randomised controlled trials, its determination has received surprisingly little attention. This article provides guidance on the specification of the target difference for the primary outcome in a sample size calculation for a two parallel group randomised controlled trial with a superiority question. METHODS This work was part of the DELTA (Difference ELicitation in TriAls) project. Draft guidance was developed by the project steering and advisory groups utilising the results of the systematic review and surveys. Findings were circulated and presented to members of the combined group at a face-to-face meeting, along with a proposed outline of the guidance document structure, containing recommendations and reporting items for a trial protocol and report. The guidance and was subsequently drafted and circulated for further comment before finalisation. RESULTS Guidance on specification of a target difference in the primary outcome for a two group parallel randomised controlled trial was produced. Additionally, a list of reporting items for protocols and trial reports was generated. CONCLUSIONS Specification of the target difference for the primary outcome is a key component of a randomized controlled trial sample size calculation. There is a need for better justification of the target difference and reporting of its specification.
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Affiliation(s)
- Jonathan A Cook
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Road, Oxford, OX3 7LD, UK.
- Health Services Research Unit, University of Aberdeen, Health Sciences Building, Foresthill, Aberdeen, AB25 2ZD, UK.
| | - Jenni Hislop
- Institute of Health and Society, Newcastle University, The Baddiley-Clark Building, Richardson Road, Newcastle upon Tyne, NE2 4AX, UK.
| | - Douglas G Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Road, Oxford, OX3 7LD, UK.
| | - Peter Fayers
- Population Health, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen, AB25 2ZD, UK.
- Department of Cancer Research and Molecular, Norwegian University of Science and Technology, Mailbox 8905, Trondheim, N-7491, Norway.
| | - Andrew H Briggs
- Health Economics and Health Technology Assessment, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Health Sciences Building, Foresthill, Aberdeen, AB25 2ZD, UK.
| | - John D Norrie
- Centre for Healthcare Randomised Trials (CHaRT), University of Aberdeen, Health Sciences Building, Aberdeen, AB25 2ZD, UK.
| | - Ian M Harvey
- Faculty of Medicine and Health Sciences, University of East Anglia, Elizabeth Fry Building, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Brian Buckley
- National University of Ireland, University Road, Galway, Ireland.
| | - Dean Fergusson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, 725 Parkdale Avenue, Ottawa, ON, K1Y 4E9, Canada.
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Boyd Orr Building, University Avenue, Glasgow, G12 8QQ, UK.
| | - Luke D Vale
- Institute of Health and Society, Newcastle University, The Baddiley-Clark Building, Richardson Road, Newcastle upon Tyne, NE2 4AX, UK.
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Cook JA, Hislop JM, Altman DG, Briggs AH, Fayers PM, Norrie JD, Ramsay CR, Harvey IM, Vale LD. Use of methods for specifying the target difference in randomised controlled trial sample size calculations: Two surveys of trialists' practice. Clin Trials 2014; 11:300-308. [PMID: 24603006 DOI: 10.1177/1740774514521907] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Central to the design of a randomised controlled trial (RCT) is a calculation of the number of participants needed. This is typically achieved by specifying a target difference, which enables the trial to identify a difference of a particular magnitude should one exist. Seven methods have been proposed for formally determining what the target difference should be. However, in practice, it may be driven by convenience or some other informal basis. It is unclear how aware the trialist community is of these formal methods or whether they are used. PURPOSE To determine current practice regarding the specification of the target difference by surveying trialists. METHODS Two surveys were conducted: (1) Members of the Society for Clinical Trials (SCT): participants were invited to complete an online survey through the society's email distribution list. Respondents were asked about their awareness, use of, and willingness to recommend methods; (2) Leading UK- and Ireland-based trialists: the survey was sent to UK Clinical Research Collaboration registered Clinical Trials Units, Medical Research Council UK Hubs for Trial Methodology Research, and the Research Design Services of the National Institute for Health Research. This survey also included questions about the most recent trial developed by the respondent's group. RESULTS Survey 1: Of the 1182 members on the SCT membership email distribution list, 180 responses were received (15%). Awareness of methods ranged from 69 (38%) for health economic methods to 162 (90%) for pilot study. Willingness to recommend among those who had used a particular method ranged from 56% for the opinion-seeking method to 89% for the review of evidence-base method. Survey 2: Of the 61 surveys sent out, 34 (56%) responses were received. Awareness of methods ranged from 33 (97%) for the review of evidence-base and pilot methods to 14 (41%) for the distribution method. The highest level of willingness to recommend among users was for the anchor method (87%). Based upon the most recent trial, the target difference was usually one viewed as important by a stakeholder group, mostly also viewed as a realistic difference given the interventions under evaluation, and sometimes one that led to an achievable sample size. LIMITATIONS The response rates achieved were relatively low despite the surveys being short, well presented, and having utilised reminders. CONCLUSION Substantial variations in practice exist with awareness, use, and willingness to recommend methods varying substantially. The findings support the view that sample size calculation is a more complex process than would appear to be the case from trial reports and protocols. Guidance on approaches for sample size estimation may increase both awareness and use of appropriate formal methods.
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Affiliation(s)
- Jonathan A Cook
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Jennifer M Hislop
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK
| | - Doug G Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Andrew H Briggs
- Health Economics and Health Technology Assessment, University of Glasgow, Glasgow, UK
| | - Peter M Fayers
- Population Health, University of Aberdeen, Aberdeen, UK Department of Cancer Research and Molecular, Norwegian University of Science and Technology, Trondheim, Norway
| | - John D Norrie
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Ian M Harvey
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK
| | - Luke D Vale
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK
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Hislop J, Adewuyi TE, Vale LD, Harrild K, Fraser C, Gurung T, Altman DG, Briggs AH, Fayers P, Ramsay CR, Norrie JD, Harvey IM, Buckley B, Cook JA. Methods for specifying the target difference in a randomised controlled trial: the Difference ELicitation in TriAls (DELTA) systematic review. PLoS Med 2014; 11:e1001645. [PMID: 24824338 PMCID: PMC4019477 DOI: 10.1371/journal.pmed.1001645] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2013] [Accepted: 04/04/2014] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. METHODS AND FINDINGS A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified-anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. CONCLUSIONS A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts.
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Affiliation(s)
- Jenni Hislop
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, United Kingdom
| | | | - Luke D. Vale
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Kirsten Harrild
- Population Health, University of Aberdeen, Aberdeen, United Kingdom
| | - Cynthia Fraser
- Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom
| | - Tara Gurung
- Warwick Evidence, University of Warwick, Coventry, United Kingdom
| | - Douglas G. Altman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
| | - Andrew H. Briggs
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Peter Fayers
- Population Health, University of Aberdeen, Aberdeen, United Kingdom
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Craig R. Ramsay
- Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom
| | - John D. Norrie
- Centre for Healthcare Randomised Trials, University of Aberdeen, Aberdeen, United Kingdom
| | - Ian M. Harvey
- Faculty of Health, University of East Anglia, Norwich, United Kingdom
| | | | - Jonathan A. Cook
- Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
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Cook JA, Hislop J, Adewuyi TE, Harrild K, Altman DG, Ramsay CR, Fraser C, Buckley B, Fayers P, Harvey I, Briggs AH, Norrie JD, Fergusson D, Ford I, Vale LD. Assessing methods to specify the target difference for a randomised controlled trial: DELTA (Difference ELicitation in TriAls) review. Health Technol Assess 2014; 18:v-vi, 1-175. [PMID: 24806703 PMCID: PMC4781097 DOI: 10.3310/hta18280] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND The randomised controlled trial (RCT) is widely considered to be the gold standard study for comparing the effectiveness of health interventions. Central to the design and validity of a RCT is a calculation of the number of participants needed (the sample size). The value used to determine the sample size can be considered the 'target difference'. From both a scientific and an ethical standpoint, selecting an appropriate target difference is of crucial importance. Determination of the target difference, as opposed to statistical approaches to calculating the sample size, has been greatly neglected though a variety of approaches have been proposed the current state of the evidence is unclear. OBJECTIVES The aim was to provide an overview of the current evidence regarding specifying the target difference in a RCT sample size calculation. The specific objectives were to conduct a systematic review of methods for specifying a target difference; to evaluate current practice by surveying triallists; to develop guidance on specifying the target difference in a RCT; and to identify future research needs. DESIGN The biomedical and social science databases searched were MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, Education Resources Information Center (ERIC) and Scopus for in-press publications. All were searched from 1966 or the earliest date of the database coverage and searches were undertaken between November 2010 and January 2011. There were three interlinked components: (1) systematic review of methods for specifying a target difference for RCTs - a comprehensive search strategy involving an electronic literature search of biomedical and some non-biomedical databases and clinical trials textbooks was carried out; (2) identification of current trial practice using two surveys of triallists - members of the Society for Clinical Trials (SCT) were invited to complete an online survey and respondents were asked about their awareness and use of, and willingness to recommend, methods; one individual per triallist group [UK Clinical Research Collaboration (UKCRC)-registered Clinical Trials Units (CTUs), Medical Research Council (MRC) UK Hubs for Trials Methodology Research and National Institute for Health Research (NIHR) UK Research Design Services (RDS)] was invited to complete a survey; (3) production of a structured guidance document to aid the design of future trials - the draft guidance was developed utilising the results of the systematic review and surveys by the project steering and advisory groups. SETTING Methodological review incorporating electronic searches, review of books and guidelines, two surveys of experts (membership of an international society and UK- and Ireland-based triallists) and development of guidance. PARTICIPANTS The two surveys were sent out to membership of the SCT and UK- and Ireland-based triallists. INTERVENTIONS The review focused on methods for specifying the target difference in a RCT. It was not restricted to any type of intervention or condition. MAIN OUTCOME MEASURES Methods for specifying the target difference for a RCT were considered. RESULTS The search identified 11,485 potentially relevant studies. In total, 1434 were selected for full-text assessment and 777 were included in the review. Seven methods to specify the target difference for a RCT were identified - anchor, distribution, health economic, opinion-seeking, pilot study, review of evidence base (RoEB) and standardised effect size (SES) - each having important variations in implementation. A total of 216 of the included studies used more than one method. A total of 180 (15%) responses to the SCT survey were received, representing 13 countries. Awareness of methods ranged from 38% (n =69) for the health economic method to 90% (n =162) for the pilot study. Of the 61 surveys sent out to UK triallist groups, 34 (56%) responses were received. Awareness ranged from 97% (n =33) for the RoEB and pilot study methods to only 41% (n =14) for the distribution method. Based on the most recent trial, all bar three groups (91%, n =30) used a formal method. Guidance was developed on the use of each method and the reporting of the sample size calculation in a trial protocol and results paper. CONCLUSIONS There is a clear need for greater use of formal methods to determine the target difference and better reporting of its specification. Raising the standard of RCT sample size calculations and the corresponding reporting of them would aid health professionals, patients, researchers and funders in judging the strength of the evidence and ensuring better use of scarce resources. FUNDING The Medical Research Council UK and the National Institute for Health Research Joint Methodology Research programme.
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Affiliation(s)
- Jonathan A Cook
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Jennifer Hislop
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | | | - Kirsten Harrild
- Medical Statistics Team, University of Aberdeen, Aberdeen, UK
| | - Douglas G Altman
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Cynthia Fraser
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Brian Buckley
- Department of General Practice, National University of Ireland, Galway, Ireland
| | - Peter Fayers
- Population Health, University of Aberdeen, Aberdeen, UK
| | - Ian Harvey
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK
| | - Andrew H Briggs
- Health Economics and Health Technology Assessment, University of Glasgow, Glasgow, UK
| | - John D Norrie
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | | | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Luke D Vale
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
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Burr JM, Campbell MK, Campbell SE, Francis JJ, Greene A, Hernández R, Hopkins D, McCann SK, Vale LD. Developing the clinical components of a complex intervention for a glaucoma screening trial: a mixed methods study. BMC Med Res Methodol 2011; 11:54. [PMID: 21510850 PMCID: PMC3112192 DOI: 10.1186/1471-2288-11-54] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2010] [Accepted: 04/21/2011] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Glaucoma is a leading cause of avoidable blindness worldwide. Open angle glaucoma is the most common type of glaucoma. No randomised controlled trials have been conducted evaluating the effectiveness of glaucoma screening for reducing sight loss. It is unclear what the most appropriate intervention to be evaluated in any glaucoma screening trial would be. The purpose of this study was to develop the clinical components of an intervention for evaluation in a glaucoma (open angle) screening trial that would be feasible and acceptable in a UK eye-care service. METHODS A mixed-methods study, based on the Medical Research Council (MRC) framework for complex interventions, integrating qualitative (semi-structured interviews with 46 UK eye-care providers, policy makers and health service commissioners), and quantitative (economic modelling) methods. Interview data were synthesised and used to revise the screening interventions compared within an existing economic model. RESULTS The qualitative data indicated broad based support for a glaucoma screening trial to take place in primary care, using ophthalmic trained technical assistants supported by optometry input. The precise location should be tailored to local circumstances. There was variability in opinion around the choice of screening test and target population. Integrating the interview findings with cost-effectiveness criteria reduced 189 potential components to a two test intervention including either optic nerve photography or screening mode perimetry (a measure of visual field sensitivity) with or without tonometry (a measure of intraocular pressure). It would be more cost-effective, and thus acceptable in a policy context, to target screening for open angle glaucoma to those at highest risk but for both practicality and equity arguments the optimal strategy was screening a general population cohort beginning at age forty. CONCLUSIONS Interventions for screening for open angle glaucoma that would be feasible from a service delivery perspective were identified. Integration within an economic modelling framework explicitly highlighted the trade-off between cost-effectiveness, feasibility and equity. This study exemplifies the MRC recommendation to integrate qualitative and quantitative methods in developing complex interventions. The next step in the development pathway should encompass the views of service users.
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Andrews PJD, Avenell A, Noble DW, Campbell MK, Croal BL, Simpson WG, Vale LD, Battison CG, Jenkinson DJ, Cook JA. Randomised trial of glutamine, selenium, or both, to supplement parenteral nutrition for critically ill patients. BMJ 2011; 342:d1542. [PMID: 21415104 DOI: 10.1136/bmj.d1542] [Citation(s) in RCA: 264] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To determine whether inclusion of glutamine, selenium, or both in a standard isonitrogenous, isocaloric preparation of parenteral nutrition influenced new infections and mortality among critically ill patients. DESIGN Randomised, double blinded, factorial, controlled trial. SETTING Level 2 and 3 (or combined) critical care units in Scotland. All 22 units were invited, and 10 participated. PARTICIPANTS 502 adults in intensive care units and high dependency units for ≥ 48 hours, with gastrointestinal failure and requiring parenteral nutrition. INTERVENTIONS Parenteral glutamine (20.2 g/day) or selenium (500 μg/day), or both, for up to seven days. MAIN OUTCOME MEASURES Primary outcomes were participants with new infections in the first 14 days and mortality. An intention to treat analysis and a prespecified analysis of patients who received ≥ 5 days of the trial intervention are presented. Secondary outcomes included critical care unit and acute hospital lengths of stay, days of antibiotic use, and modified SOFA (Sepsis-related Organ Failure Assessment) score. RESULTS Selenium supplementation did not significantly affect patients developing a new infection (126/251 v 139/251, odds ratio 0.81 (95% CI 0.57 to 1.15)), except for those who had received ≥ 5 days of supplementation (odds ratio 0.53 (0.30 to 0.93)). There was no overall effect of glutamine on new infections (134/250 v 131/252, odds ratio 1.07 (0.75 to 1.53)), even if patients received ≥ 5 days of supplementation (odds ratio 0.99 (0.56 to 1.75)). Six month mortality was not significantly different for selenium (107/251 v 114/251, odds ratio 0.89 (0.62 to 1.29)) or glutamine (115/250 v 106/252, 1.18 (0.82 to 1.70)). Length of stay, days of antibiotic use, and modified SOFA score were not significantly affected by selenium or glutamine supplementation. CONCLUSIONS The primary (intention to treat) analysis showed no effect on new infections or on mortality when parenteral nutrition was supplemented with glutamine or selenium. Patients who received parenteral nutrition supplemented with selenium for ≥ 5 days did show a reduction in new infections. This finding requires confirmation. Trial registration Current Controlled Trials ISRCTN87144826.
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Affiliation(s)
- Peter J D Andrews
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH4 2XU, UK.
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Sullivan FM, Swan IRC, Donnan PT, Morrison JM, Smith BH, McKinstry B, Davenport RJ, Vale LD, Clarkson JE, Hernández R, Stewart K, Hammersley V, Hayavi S, McAteer A, Gray D, Daly F. A randomised controlled trial of the use of aciclovir and/or prednisolone for the early treatment of Bell's palsy: the BELLS study. Health Technol Assess 2010; 13:iii-iv, ix-xi 1-130. [PMID: 19833052 DOI: 10.3310/hta13470] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE To determine whether oral prednisolone or aciclovir, used separately or in combination, early in the course of Bell's palsy, improves the chances of recovery at 3 and 9 months. DESIGN A 2 x 2 factorial randomised double-blind trial. Patients were randomly assigned to treatment by an automated telephone service using a permuted block randomisation technique with block sizes of four or eight, and no stratification. SETTING Mainland Scotland, with referrals mainly from general practice to 17 hospital trial sites. PARTICIPANTS Adults (aged 16 years or older) with unilateral facial nerve weakness of no identifiable cause presenting to primary care, the emergency department or NHS24 within 72 hours of symptom onset. INTERVENTIONS Patients were randomised to receive active preparations or placebo for 10 days: (1) prednisolone (50 mg per day, 2 x 25-mg capsules) and aciclovir (2000 mg per day, 5 x 400-mg capsules); (2) prednisolone and placebo (lactose, indistinguishable); (3) aciclovir and placebo; and (4) placebo and placebo. OUTCOME MEASURES The primary outcome was recovery of facial function assessed by the House-Brackmann scale. Secondary outcomes included health status, pain, self-perceived appearance and cost-effectiveness. RESULTS Final outcomes were available for 496 patients, balanced for gender; mean age 44 years; initial facial paralysis moderate to severe. One half of patients initiated treatment within 24 hours of onset of symptoms, one-third within 24-48 hours and the remainder within 48-72 hours. Of the completed patients, 357 had recovered by 3 months and 80 at 9 months, leaving 59 with a residual deficit. There were significant differences in complete recovery at 3 months between the prednisolone comparison groups (83.0% for prednisolone, 63.6% for no prednisolone, a difference of + 19.4%; 95% confidence interval (CI): + 11.7% to + 27.1%, p < 0.001). The number needed to treat (NNT) in order to achieve one additional complete recovery was 6 (95% CI: 4 to 9). There was no significant difference between the aciclovir comparison groups (71.2% for aciclovir and 75.7% for no aciclovir). Nine-month assessments of patients recovered were 94.4% for prednisolone compared with 81.6% for no prednisolone, a difference of + 12.8% (95% CI: + 7.2% to + 18.4%, p < 0.001); the NNT was 8 (95% CI: 6 to 14). Proportions recovered at 9 months were 85.4% for aciclovir and 90.8% for no aciclovir, a difference of -5.3%. There was no significant prednisolone-aciclovir interaction at 3 months or at 9 months. Outcome differences by individual treatment (the four-arm model) showed significant differences. At 3 months the recovery rate was 86.3% in the prednisolone treatment group, 79.7% in the aciclovir-prednisolone group, 64.7% in the placebo group and 62.5% in the aciclovir group. At 9 months the recovery rates were respectively 96.1%, 92.7%, 85.3% and 78.1%. The increase in recovery rate conferred by the addition of prednisolone (both for prednisolone over placebo and for aciclovir-prednisolone over aciclovir) is highly statistically significant (p < 0.001). There were no significant differences in secondary measures apart from Health Utilities Index Mark 3 (HUI3) at 9 months in those treated with prednisolone. CONCLUSIONS This study provided robust evidence to support the early use of oral prednisolone in Bell's palsy as an effective treatment which may be considered cost-effective. Treatment with aciclovir, either alone or with steroids, had no effect on outcome.
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Affiliation(s)
- F M Sullivan
- Scottish School of Primary Care, University of Dundee, UK
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Abstract
OBJECTIVE Colorectal cancer is one of the most common cancers and the standard surgical treatment for this cancer is open resection (OS), but laparoscopic surgery (LS) may be an alternative treatment. In 2000, a Health Technology Assessment (HTA) review found little evidence on costs and cost-effectiveness in comparing the two methods. The evidence base has since expanded and this study systematically reviews the economic evaluations on the subject published since 2000. METHOD Systematic review of studies reporting costs and outcomes of LS vs OS for colorectal cancer. National Health Service Economic Evaluation Database (NHS EED) methods for abstract writing were followed. Studies were summarized and incremental cost-effectiveness ratios (ICER) for common outcomes were calculated. RESULTS Five studies met the inclusion criteria. LS generally had higher healthcare costs. Most studies reported longer operational time and shorter length of stay and similar long-term outcomes with LS vs OS. Only one outcome, complications, was common across all studies but results lacked consistency (e.g. in two studies, OS was less costly but more effective; in another study, LS was less costly but more effective; and in the further two studies, LS could potentially be cost effective depending on the decision-makers' willingness to pay for the health gain). CONCLUSION The evidence on cost-effectiveness is not consistent. LS was generally more costly than OS. However, the effectiveness data used in individual economic evaluation were imprecise and unreliable when compared with data from systematic reviews of effectiveness. Nevertheless, short-term benefits of LS (e.g. shorter recovery) may make LS appear less costly when productivity gains are considered.
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Affiliation(s)
- R A Hernández
- Health Economics Research Unit, Institute of Applied Health Sciences, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, Scotland, UK
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Sullivan FM, Swan IR, Donnan PT, Morrison JM, Smith BH, McKinstry B, Davenport RJ, Vale LD, Ciarkson JE, Hammersley V, Hayavi S, McAteer A, Stewart K, Daly F. Early Treatment with Prednisolone or Acyclovir in Bell’s Palsy. Clin Otolaryngol 2007. [DOI: 10.1111/j.1749-4486.2007.01573.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Sullivan FM, Swan IRC, Donnan PT, Morrison JM, Smith BH, McKinstry B, Davenport RJ, Vale LD, Clarkson JE, Hammersley V, Hayavi S, McAteer A, Stewart K, Daly F. Early treatment with prednisolone or acyclovir in Bell's palsy. N Engl J Med 2007; 357:1598-607. [PMID: 17942873 DOI: 10.1056/nejmoa072006] [Citation(s) in RCA: 379] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND Corticosteroids and antiviral agents are widely used to treat the early stages of idiopathic facial paralysis (i.e., Bell's palsy), but their effectiveness is uncertain. METHODS We conducted a double-blind, placebo-controlled, randomized, factorial trial involving patients with Bell's palsy who were recruited within 72 hours after the onset of symptoms. Patients were randomly assigned to receive 10 days of treatment with prednisolone, acyclovir, both agents, or placebo. The primary outcome was recovery of facial function, as rated on the House-Brackmann scale. Secondary outcomes included quality of life, appearance, and pain. RESULTS Final outcomes were assessed for 496 of 551 patients who underwent randomization. At 3 months, the proportions of patients who had recovered facial function were 83.0% in the prednisolone group as compared with 63.6% among patients who did not receive prednisolone (P<0.001) and 71.2% in the acyclovir group as compared with 75.7% among patients who did not receive acyclovir (adjusted P=0.50). After 9 months, these proportions were 94.4% for prednisolone and 81.6% for no prednisolone (P<0.001) and 85.4% for acyclovir and 90.8% for no acyclovir (adjusted P=0.10). For patients treated with both drugs, the proportions were 79.7% at 3 months (P<0.001) and 92.7% at 9 months (P<0.001). There were no clinically significant differences between the treatment groups in secondary outcomes. There were no serious adverse events in any group. CONCLUSIONS In patients with Bell's palsy, early treatment with prednisolone significantly improves the chances of complete recovery at 3 and 9 months. There is no evidence of a benefit of acyclovir given alone or an additional benefit of acyclovir in combination with prednisolone. (Current Controlled Trials number, ISRCTN71548196 [controlled-trials.com].).
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Affiliation(s)
- Frank M Sullivan
- Scottish School of Primary Care, University of Dundee, Dundee, United Kingdom.
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Andrews PJD, Avenell A, Noble DW, Campbell MK, Battison CG, Croal BL, Simpson WG, Norrie J, Vale LD, Cook J, de Verteuil R, Milne AC. Randomised trial of glutamine and selenium supplemented parenteral nutrition for critically ill patients. Protocol Version 9, 19 February 2007 known as SIGNET (Scottish Intensive care Glutamine or seleNium Evaluative Trial). Trials 2007; 8:25. [PMID: 17883854 PMCID: PMC2082027 DOI: 10.1186/1745-6215-8-25] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2007] [Accepted: 09/20/2007] [Indexed: 11/22/2022] Open
Abstract
Background Mortality rates in the Intensive Care Unit and subsequent hospital mortality rates in the UK remain high. Infections in Intensive Care are associated with a 2–3 times increased risk of death. It is thought that under conditions of severe metabolic stress glutamine becomes "conditionally essential". Selenium is an essential trace element that has antioxidant and anti-inflammatory properties. Approximately 23% of patients in Intensive Care require parenteral nutrition and glutamine and selenium are either absent or present in low amounts. Both glutamine and selenium have the potential to influence the immune system through independent biochemical pathways. Systematic reviews suggest that supplementing parenteral nutrition in critical illness with glutamine or selenium may reduce infections and mortality. Pilot data has shown that more than 50% of participants developed infections, typically resistant organisms. We are powered to show definitively whether supplementation of PN with either glutamine or selenium is effective at reducing new infections in critically ill patients. Methods/design 2 × 2 factorial, pragmatic, multicentre, double-blind, randomised controlled trial. The trial has an enrolment target of 500 patients. Inclusion criteria include: expected to be in critical care for at least 48 hours, aged 16 years or over, patients who require parenteral nutrition and are expected to have at least half their daily nutritional requirements given by that route. Allocation is to one of four iso-caloric, iso-nitrogenous groups: glutamine, selenium, both glutamine & selenium or no additional glutamine or selenium. Trial supplementation is given for up to seven days on the Intensive Care Unit and subsequent wards if practicable. The primary outcomes are episodes of infection in the 14 days after starting trial nutrition and mortality. Secondary outcomes include antibiotic usage, length of hospital stay, quality of life and cost-effectiveness. Discussion To date more than 285 patients have been recruited to the trial from 10 sites in Scotland. Recruitment is due to finish in August 2008 with a further six months follow up. We expect to report the results of the trial in summer 2009. Trial registration This trial is registered with the International Standard Randomised Controlled Trial Number system. ISRCTN87144826
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Affiliation(s)
- Peter JD Andrews
- Department of Anaesthesia, Critical Care & Pain Medicine, University of Edinburgh & Consultant, Critical Care, Western General Hospital Lothian University Hospitals Division, Edinburgh EH4 2XU, Scotland, UK
| | - Alison Avenell
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - David W Noble
- Department of Anaesthetics & Intensive Care, Aberdeen Royal Infirmary, Foresterhill, Aberdeen AB25 2ZN Scotland, UK
| | - Marion K Campbell
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - Claire G Battison
- Department of Anaesthesia, Critical Care & Pain Medicine, University of Edinburgh & Consultant, Critical Care, Western General Hospital Lothian University Hospitals Division, Edinburgh EH4 2XU, Scotland, UK
| | - Bernard L Croal
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - William G Simpson
- Department of Clinical Biochemistry, Aberdeen Royal Infirmary, Foresterhill, Aberdeen AB25 2ZN, Scotland, UK
| | - John Norrie
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - Luke D Vale
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
- Health Economics Research Unit, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - Jonathon Cook
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - Robyn de Verteuil
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
| | - Anne C Milne
- Health Services Research Unit, Health Sciences Building, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
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Kilonzo MM, Vale LD, Cook JA, Milne AC, Stephen AI, Avenell A. A cost-utility analysis of multivitamin and multimineral supplements in men and women aged 65 years and over. Clin Nutr 2007; 26:364-70. [PMID: 17198742 DOI: 10.1016/j.clnu.2006.11.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2006] [Revised: 08/31/2006] [Accepted: 11/08/2006] [Indexed: 11/22/2022]
Abstract
BACKGROUND & AIMS As people age there is a progressive dysregulation of the immune system that may lead to an increased risk of infections, which may precipitate hospital admission in people with chronic heart or respiratory diseases. Mineral and vitamin supplementation in older people could therefore influence infections in older people. However, the evidence from the available randomised controlled trials (RCTs) is mixed. The aim of the study was to assess the relative efficiency of multivitamin and multimineral supplementation compared with no supplementation. METHODS Cost-utility analysis alongside an RCT. Participants aged 65 years or over from six general practices in Grampian, Scotland, were studied. They were randomised to one tablet daily of either a multivitamin and multimineral supplement or matching placebo. Exclusion criteria were use of mineral, vitamin or fish oil supplements in the previous 3 months (1 month for water soluble vitamins), vitamin B12 injection in the last 3 months. RESULTS Nine hundred and ten participants were recruited (454 placebo and 456 supplementation). Use of health service resources and costs were similar between the two groups. The supplementation arm was more costly although this was not statistically significant ( pound15 per person, 95% CI-3.75 to 34.95). After adjusting for minimisation and baseline EQ-5D scores supplementation was associated with fewer QALYs per person (-0.018, 95% CI-0.04 to 0.002). It was highly unlikely that supplementation would be considered cost effective. CONCLUSIONS The evidence from this study suggests that it is highly unlikely that supplementation could be considered cost effective.
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Affiliation(s)
- Mary M Kilonzo
- Health Economics Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK.
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McNeill G, Avenell A, Campbell MK, Cook JA, Hannaford PC, Kilonzo MM, Milne AC, Ramsay CR, Seymour DG, Stephen AI, Vale LD. Effect of multivitamin and multimineral supplementation on cognitive function in men and women aged 65 years and over: a randomised controlled trial. Nutr J 2007; 6:10. [PMID: 17474991 PMCID: PMC1872030 DOI: 10.1186/1475-2891-6-10] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2006] [Accepted: 05/02/2007] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Observational studies have frequently reported an association between cognitive function and nutrition in later life but randomised trials of B vitamins and antioxidant supplements have mostly found no beneficial effect. We examined the effect of daily supplementation with 11 vitamins and 5 minerals on cognitive function in older adults to assess the possibility that this could help to prevent cognitive decline. METHODS The study was carried out as part of a randomised double blind placebo controlled trial of micronutrient supplementation based in six primary care health centres in North East Scotland. 910 men and women aged 65 years and over living in the community were recruited and randomised: 456 to active treatment and 454 to placebo. The active treatment consisted of a single tablet containing eleven vitamins and five minerals in amounts ranging from 50-210 % of the UK Reference Nutrient Intake or matching placebo tablet taken daily for 12 months. Digit span forward and verbal fluency tests, which assess immediate memory and executive functioning respectively, were conducted at the start and end of the intervention period. Risk of micronutrient deficiency at baseline was assessed by a simple risk questionnaire. RESULTS For digit span forward there was no evidence of an effect of supplements in all participants or in sub-groups defined by age or risk of deficiency. For verbal fluency there was no evidence of a beneficial effect in the whole study population but there was weak evidence for a beneficial effect of supplementation in the two pre-specified subgroups: in those aged 75 years and over (n 290; mean difference between supplemented and placebo groups 2.8 (95% CI -0.6, 6.2) units) and in those at increased risk of micronutrient deficiency assessed by the risk questionnaire (n 260; mean difference between supplemented and placebo groups 2.5 (95% CI -1.0, 6.1) units). CONCLUSION The results provide no evidence for a beneficial effect of daily multivitamin and multimineral supplements on these domains of cognitive function in community-living people over 65 years. However, the possibility of beneficial effects in older people and those at greater risk of nutritional deficiency deserves further attention.
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Affiliation(s)
- Geraldine McNeill
- Department of Environmental and Occupational Medicine, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Alison Avenell
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Marion K Campbell
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Jonathan A Cook
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Philip C Hannaford
- Department of General Practice and Primary Care, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Mary M Kilonzo
- Health Economics Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Anne C Milne
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - D Gwyn Seymour
- Department of Medicine for the Elderly, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Audrey I Stephen
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Luke D Vale
- Health Services Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
- Health Economics Research Unit, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
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Avenell A, Campbell MK, Cook JA, Milne AC, Ramsay CR, Stephen AI, Kilonzo MM, Vale LD, McNeill G, Seymour DG. The key role of micronutrients. Clin Nutr 2007; 26:159; author reply 160. [PMID: 16934374 DOI: 10.1016/j.clnu.2006.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2006] [Accepted: 07/07/2006] [Indexed: 11/16/2022]
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Avenell A, Campbell MK, Cook JA, Hannaford PC, Kilonzo MM, McNeill G, Milne AC, Ramsay CR, Seymour DG, Stephen AI, Vale LD. Effect of multivitamin and multimineral supplements on morbidity from infections in older people (MAVIS trial): pragmatic, randomised, double blind, placebo controlled trial. BMJ 2005; 331:324-9. [PMID: 16081445 PMCID: PMC1183131 DOI: 10.1136/bmj.331.7512.324] [Citation(s) in RCA: 68] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/09/2005] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To examine whether supplementation with multivitamins and multiminerals influences self reported days of infection, use of health services, and quality of life in people aged 65 or over. DESIGN Randomised, placebo controlled trial, with blinding of participants, outcome assessors, and investigators. SETTING Communities associated with six general practices in Grampian, Scotland. PARTICIPANTS 910 men and women aged 65 or over who did not take vitamins or minerals. INTERVENTIONS Daily multivitamin and multimineral supplementation or placebo for one year. MAIN OUTCOME MEASURES Primary outcomes were contacts with primary care for infections, self reported days of infection, and quality of life. Secondary outcomes included antibiotic prescriptions, hospital admissions, adverse events, and compliance. RESULTS Supplementation did not significantly affect contacts with primary care and days of infection per person (incidence rate ratio 0.96, 95% confidence interval 0.78 to 1.19 and 1.07, 0.90 to 1.27). Quality of life was not affected by supplementation. No statistically significant findings were found for secondary outcomes or subgroups. CONCLUSION Routine multivitamin and multimineral supplementation of older people living at home does not affect self reported infection related morbidity. TRIAL REGISTRATION ISRCTN: 66376460.
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Affiliation(s)
- Alison Avenell
- Health Services Research Unit, School of Medicine, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD.
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Gilbert FJ, Grant AM, Gillan MGC, Vale LD, Campbell MK, Scott NW, Knight DJ, Wardlaw D. Low back pain: influence of early MR imaging or CT on treatment and outcome--multicenter randomized trial. Radiology 2004; 231:343-51. [PMID: 15031430 DOI: 10.1148/radiol.2312030886] [Citation(s) in RCA: 96] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
PURPOSE To establish whether early use of magnetic resonance (MR) imaging or computed tomography (CT) influences treatment and outcome of patients with low back pain (LBP) and whether it is cost-effective. MATERIALS AND METHODS In a multicenter randomized study, two imaging policies for LBP were compared in 782 participants with symptomatic lumbar spine disorders who were referred to orthopedists or neurosurgeons. Participants were randomly allocated to early (393 participants; mean age, 43.9 years; range, 16-82 years) or delayed selective (389 participants; mean age, 42.8 years; range, 14-82 years) imaging groups. Delayed selective imaging referred to imaging restricted to patients in whom a clear clinical need subsequently developed. Main outcome measures were Aberdeen Low Back Pain (ALBP) score, Short Form 36 (SF-36) score (for multidimensional health status), EuroQol (EQ-5D) score (for quality-adjusted life-year [QALY] estimates), and healthcare resource use at 8 and 24 months after randomization. Data were evaluated with analysis of covariance, ordinal logistic regression analysis, and chi(2) and Mann-Whitney tests. RESULTS Both groups showed improvement in ALBP score, but this was greater in the early group (adjusted mean difference between groups, -3.05 points [95% CI: -5.16, -0.95; P =.005] and -3.62 points [95% CI: -5.92, -1.32; P =.002] at 8 and 24 months, respectively). Scores for SF-36 (bodily pain domain) and EQ-5D were also significantly better at 24 months. Clinical treatment was similar in both groups. Differences in total costs reflected cost of imaging. Imaging provided an adjusted mean additional QALY of 0.041 during 24 months at a mean incremental cost per QALY of $2,124. CONCLUSION Early use of imaging does not appear to affect treatment overall. Decisions about the use of imaging depend on judgments concerning whether the small observed improvement in outcome justifies additional cost.
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Affiliation(s)
- Fiona J Gilbert
- Department of Radiology, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland.
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Daly CD, Campbell MK, MacLeod AM, Cody DJ, Vale LD, Grant AM, Donaldson C, Wallace SA, Lawrence PD, Khan IH. Do the Y-set and double-bag systems reduce the incidence of CAPD peritonitis? A systematic review of randomized controlled trials. Nephrol Dial Transplant 2001; 16:341-7. [PMID: 11158410 DOI: 10.1093/ndt/16.2.341] [Citation(s) in RCA: 54] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Peritonitis is the most frequent serious complication of continuous ambulatory peritoneal dialysis (CAPD). It has a major influence on the number of patients switching from CAPD to haemodialysis and has probably restricted the wider acceptance and uptake of CAPD as an alternative mode of dialysis. This systematic review sought to determine if modifications of the transfer set (Y-set or double-bag systems) used in CAPD exchanges are associated with a reduction in peritonitis and an improvement in other relevant outcomes. METHODS Based on a comprehensive search strategy, we undertook a systematic review of randomized or quasi-randomized controlled trials comparing double-bag and/or Y-set CAPD exchange systems with standard systems, or comparing double-bag with Y-set systems, in patients with end-stage renal disease (ESRD) treated with CAPD. Only published data were used. Data were abstracted by a single investigator onto a standard form and subsequently entered into Review Manager 4.0.4. Its statistical package, Metaview 3.1, calculated an odds ratio (OR) for dichotomous data and a (weighted) mean difference for continuous data with 95% confidence intervals. RESULTS Twelve eligible trials with a total of 991 randomized patients were identified. In trials comparing either the Y-set or double-bag systems with the standard systems, significantly fewer patients (133/363 vs 158/263; OR 0.33, 95% CI 0.24-0.46) experienced peritonitis and the number of patient-months on CAPD per episode of peritonitis was consistently greater. When the double-bag systems were compared with the Y-set systems significantly fewer patients experienced peritonitis (44/154 vs 66/138; OR 0.44, 95% CI 0.27-0.71) and the number of patient-months on CAPD per episode of peritonitis was also greater. CONCLUSIONS Double-bag systems should be the preferred exchange systems in CAPD.
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Affiliation(s)
- C D Daly
- Department of Medicine and Therapeutics, University of Aberdeen, Aberdeen, UK
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