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Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool

Thousands of observational studies have linked vitamin D deficiency with numerous diseases, but randomised controlled trials (RCTs) often fail to show benefit of supplementation. Population characteristics and trial design have long been suspected to undermine power but were not systematically inves...

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Autores principales: Wyse, Jason, Mangan, Rebecca, Zgaga, Lina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144427/
https://www.ncbi.nlm.nih.gov/pubmed/34031451
http://dx.doi.org/10.1038/s41598-021-90019-7
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author Wyse, Jason
Mangan, Rebecca
Zgaga, Lina
author_facet Wyse, Jason
Mangan, Rebecca
Zgaga, Lina
author_sort Wyse, Jason
collection PubMed
description Thousands of observational studies have linked vitamin D deficiency with numerous diseases, but randomised controlled trials (RCTs) often fail to show benefit of supplementation. Population characteristics and trial design have long been suspected to undermine power but were not systematically investigated. We propose a flexible generative model to characterise benefit of vitamin D supplementation at the individual level, and use this to quantify power in RCTs. The model can account for seasonality and population heterogeneity. In a simulated 1-year trial with 1000 participants per arm and assuming a 25-hydroxyvitamin D (25OHD) increase of 20 nmol/L due to the intervention, with baseline 25OHD in the population of 15, 35, 50, 60 and 75 nmol/L, the power to detect intervention effect was 77%, 99%, 95%, 68% and 19%, respectively. The number of participants required per arm to achieve 80% power according to baseline 25OHD of 15–60 nmol/L was 1200, 400, 600 and 1400, respectively. As expected, larger increases in 25OHD due to supplementation improved power in certain scenarios. For a population baseline of 50 nmol/L, with 1500 participants in each arm, there was 100% power to detect a 20 nmol/L 25OHD increase while it was 76% for a 10 nmol/L increase. Population characteristics and trial design, including temporal considerations, have a dramatic impact on power and required sample size in vitamin D RCTs.
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spelling pubmed-81444272021-05-25 Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool Wyse, Jason Mangan, Rebecca Zgaga, Lina Sci Rep Article Thousands of observational studies have linked vitamin D deficiency with numerous diseases, but randomised controlled trials (RCTs) often fail to show benefit of supplementation. Population characteristics and trial design have long been suspected to undermine power but were not systematically investigated. We propose a flexible generative model to characterise benefit of vitamin D supplementation at the individual level, and use this to quantify power in RCTs. The model can account for seasonality and population heterogeneity. In a simulated 1-year trial with 1000 participants per arm and assuming a 25-hydroxyvitamin D (25OHD) increase of 20 nmol/L due to the intervention, with baseline 25OHD in the population of 15, 35, 50, 60 and 75 nmol/L, the power to detect intervention effect was 77%, 99%, 95%, 68% and 19%, respectively. The number of participants required per arm to achieve 80% power according to baseline 25OHD of 15–60 nmol/L was 1200, 400, 600 and 1400, respectively. As expected, larger increases in 25OHD due to supplementation improved power in certain scenarios. For a population baseline of 50 nmol/L, with 1500 participants in each arm, there was 100% power to detect a 20 nmol/L 25OHD increase while it was 76% for a 10 nmol/L increase. Population characteristics and trial design, including temporal considerations, have a dramatic impact on power and required sample size in vitamin D RCTs. Nature Publishing Group UK 2021-05-24 /pmc/articles/PMC8144427/ /pubmed/34031451 http://dx.doi.org/10.1038/s41598-021-90019-7 Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wyse, Jason
Mangan, Rebecca
Zgaga, Lina
Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool
title Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool
title_full Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool
title_fullStr Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool
title_full_unstemmed Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool
title_short Power determination in vitamin D randomised control trials and characterising factors affecting it through a novel simulation-based tool
title_sort power determination in vitamin d randomised control trials and characterising factors affecting it through a novel simulation-based tool
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144427/
https://www.ncbi.nlm.nih.gov/pubmed/34031451
http://dx.doi.org/10.1038/s41598-021-90019-7
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