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Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial
BACKGROUND: General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) is a multicentre, individually randomised controlled trial aiming to compare the use of intermittent retrospective continuous glucose monitoring (r-CGM) to usual care in patient...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354399/ https://www.ncbi.nlm.nih.gov/pubmed/30700324 http://dx.doi.org/10.1186/s13063-018-3126-1 |
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author | Thuraisingam, Sharmala Chondros, Patty Catchpool, Max Dalziel, Kim Manski-Nankervis, Jo-Anne Speight, Jane Holmes-Truscott, Elizabeth Audehm, Ralph Chiang, Jason Blackberry, Irene O’Neal, David Khunti, Kamlesh Best, James Furler, John |
author_facet | Thuraisingam, Sharmala Chondros, Patty Catchpool, Max Dalziel, Kim Manski-Nankervis, Jo-Anne Speight, Jane Holmes-Truscott, Elizabeth Audehm, Ralph Chiang, Jason Blackberry, Irene O’Neal, David Khunti, Kamlesh Best, James Furler, John |
author_sort | Thuraisingam, Sharmala |
collection | PubMed |
description | BACKGROUND: General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) is a multicentre, individually randomised controlled trial aiming to compare the use of intermittent retrospective continuous glucose monitoring (r-CGM) to usual care in patients with type 2 diabetes attending general practice. The study protocol was published in the British Medical Journal Open and described the principal features of the statistical methods that will be used to analyse the trial data. This paper provides greater detail on the statistical analysis plan, including background and justification for the statistical methods chosen, in accordance with SPIRIT guidelines. OBJECTIVE: To describe in detail the data management process and statistical methods that will be used to analyse the trial data. METHODS: An overview of the trial design and primary and secondary research questions are provided. Sample size assumptions and calculations are explained, and randomisation and data management processes are described in detail. The planned statistical analyses for primary and secondary outcomes and sub-group analyses are specified along with the intended table layouts for presentation of the results. CONCLUSION: In accordance with best practice, all analyses outlined in the document are based on the aims of the study and have been pre-specified prior to the completion of data collection and outcome analyses. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12616001372471. Registered on 3 August 2016. |
format | Online Article Text |
id | pubmed-6354399 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63543992019-02-07 Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial Thuraisingam, Sharmala Chondros, Patty Catchpool, Max Dalziel, Kim Manski-Nankervis, Jo-Anne Speight, Jane Holmes-Truscott, Elizabeth Audehm, Ralph Chiang, Jason Blackberry, Irene O’Neal, David Khunti, Kamlesh Best, James Furler, John Trials Update BACKGROUND: General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) is a multicentre, individually randomised controlled trial aiming to compare the use of intermittent retrospective continuous glucose monitoring (r-CGM) to usual care in patients with type 2 diabetes attending general practice. The study protocol was published in the British Medical Journal Open and described the principal features of the statistical methods that will be used to analyse the trial data. This paper provides greater detail on the statistical analysis plan, including background and justification for the statistical methods chosen, in accordance with SPIRIT guidelines. OBJECTIVE: To describe in detail the data management process and statistical methods that will be used to analyse the trial data. METHODS: An overview of the trial design and primary and secondary research questions are provided. Sample size assumptions and calculations are explained, and randomisation and data management processes are described in detail. The planned statistical analyses for primary and secondary outcomes and sub-group analyses are specified along with the intended table layouts for presentation of the results. CONCLUSION: In accordance with best practice, all analyses outlined in the document are based on the aims of the study and have been pre-specified prior to the completion of data collection and outcome analyses. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12616001372471. Registered on 3 August 2016. BioMed Central 2019-01-30 /pmc/articles/PMC6354399/ /pubmed/30700324 http://dx.doi.org/10.1186/s13063-018-3126-1 Text en © The Author(s). 2019 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. |
spellingShingle | Update Thuraisingam, Sharmala Chondros, Patty Catchpool, Max Dalziel, Kim Manski-Nankervis, Jo-Anne Speight, Jane Holmes-Truscott, Elizabeth Audehm, Ralph Chiang, Jason Blackberry, Irene O’Neal, David Khunti, Kamlesh Best, James Furler, John Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial |
title | Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial |
title_full | Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial |
title_fullStr | Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial |
title_full_unstemmed | Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial |
title_short | Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial |
title_sort | update on the general practice optimising structured monitoring to improve clinical outcomes in type 2 diabetes (gp-osmotic) trial: statistical analysis plan for a multi-centre randomised controlled trial |
topic | Update |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354399/ https://www.ncbi.nlm.nih.gov/pubmed/30700324 http://dx.doi.org/10.1186/s13063-018-3126-1 |
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