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Sample size and power determination when limited preliminary information is available
BACKGROUND: We describe a novel strategy for power and sample size determination developed for studies utilizing investigational technologies with limited available preliminary data, specifically of imaging biomarkers. We evaluated diffuse optical spectroscopic imaging (DOSI), an experimental noninv...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406943/ https://www.ncbi.nlm.nih.gov/pubmed/28446127 http://dx.doi.org/10.1186/s12874-017-0329-1 |
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author | McLaren, Christine E. Chen, Wen-Pin O’Sullivan, Thomas D. Gillen, Daniel L. Su, Min-Ying Chen, Jeon H. Tromberg, Bruce J. |
author_facet | McLaren, Christine E. Chen, Wen-Pin O’Sullivan, Thomas D. Gillen, Daniel L. Su, Min-Ying Chen, Jeon H. Tromberg, Bruce J. |
author_sort | McLaren, Christine E. |
collection | PubMed |
description | BACKGROUND: We describe a novel strategy for power and sample size determination developed for studies utilizing investigational technologies with limited available preliminary data, specifically of imaging biomarkers. We evaluated diffuse optical spectroscopic imaging (DOSI), an experimental noninvasive imaging technique that may be capable of assessing changes in mammographic density. Because there is significant evidence that tamoxifen treatment is more effective at reducing breast cancer risk when accompanied by a reduction of breast density, we designed a study to assess the changes from baseline in DOSI imaging biomarkers that may reflect fluctuations in breast density in premenopausal women receiving tamoxifen. METHOD: While preliminary data demonstrate that DOSI is sensitive to mammographic density in women about to receive neoadjuvant chemotherapy for breast cancer, there is no information on DOSI in tamoxifen treatment. Since the relationship between magnetic resonance imaging (MRI) and DOSI has been established in previous studies, we developed a statistical simulation approach utilizing information from an investigation of MRI assessment of breast density in 16 women before and after treatment with tamoxifen to estimate the changes in DOSI biomarkers due to tamoxifen. RESULTS: Three sets of 10,000 pairs of MRI breast density data with correlation coefficients of 0.5, 0.8 and 0.9 were simulated and generated and were used to simulate and generate a corresponding 5,000,000 pairs of DOSI values representing water, ctHHB, and lipid. Minimum sample sizes needed per group for specified clinically-relevant effect sizes were obtained. CONCLUSION: The simulation techniques we describe can be applied in studies of other experimental technologies to obtain the important preliminary data to inform the power and sample size calculations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-017-0329-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5406943 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54069432017-04-27 Sample size and power determination when limited preliminary information is available McLaren, Christine E. Chen, Wen-Pin O’Sullivan, Thomas D. Gillen, Daniel L. Su, Min-Ying Chen, Jeon H. Tromberg, Bruce J. BMC Med Res Methodol Research Article BACKGROUND: We describe a novel strategy for power and sample size determination developed for studies utilizing investigational technologies with limited available preliminary data, specifically of imaging biomarkers. We evaluated diffuse optical spectroscopic imaging (DOSI), an experimental noninvasive imaging technique that may be capable of assessing changes in mammographic density. Because there is significant evidence that tamoxifen treatment is more effective at reducing breast cancer risk when accompanied by a reduction of breast density, we designed a study to assess the changes from baseline in DOSI imaging biomarkers that may reflect fluctuations in breast density in premenopausal women receiving tamoxifen. METHOD: While preliminary data demonstrate that DOSI is sensitive to mammographic density in women about to receive neoadjuvant chemotherapy for breast cancer, there is no information on DOSI in tamoxifen treatment. Since the relationship between magnetic resonance imaging (MRI) and DOSI has been established in previous studies, we developed a statistical simulation approach utilizing information from an investigation of MRI assessment of breast density in 16 women before and after treatment with tamoxifen to estimate the changes in DOSI biomarkers due to tamoxifen. RESULTS: Three sets of 10,000 pairs of MRI breast density data with correlation coefficients of 0.5, 0.8 and 0.9 were simulated and generated and were used to simulate and generate a corresponding 5,000,000 pairs of DOSI values representing water, ctHHB, and lipid. Minimum sample sizes needed per group for specified clinically-relevant effect sizes were obtained. CONCLUSION: The simulation techniques we describe can be applied in studies of other experimental technologies to obtain the important preliminary data to inform the power and sample size calculations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-017-0329-1) contains supplementary material, which is available to authorized users. BioMed Central 2017-04-26 /pmc/articles/PMC5406943/ /pubmed/28446127 http://dx.doi.org/10.1186/s12874-017-0329-1 Text en © The Author(s). 2017 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 | Research Article McLaren, Christine E. Chen, Wen-Pin O’Sullivan, Thomas D. Gillen, Daniel L. Su, Min-Ying Chen, Jeon H. Tromberg, Bruce J. Sample size and power determination when limited preliminary information is available |
title | Sample size and power determination when limited preliminary information is available |
title_full | Sample size and power determination when limited preliminary information is available |
title_fullStr | Sample size and power determination when limited preliminary information is available |
title_full_unstemmed | Sample size and power determination when limited preliminary information is available |
title_short | Sample size and power determination when limited preliminary information is available |
title_sort | sample size and power determination when limited preliminary information is available |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406943/ https://www.ncbi.nlm.nih.gov/pubmed/28446127 http://dx.doi.org/10.1186/s12874-017-0329-1 |
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