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Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies
Human tumor xenograft studies are the primary means to evaluate the biological activity of anticancer agents in late-stage preclinical drug discovery. The variability in the growth rate of human tumors established in mice and the small sample sizes make rigorous statistical analysis critical. The mo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264612/ https://www.ncbi.nlm.nih.gov/pubmed/25574127 http://dx.doi.org/10.4137/CIN.S13974 |
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author | Hather, Gregory Liu, Ray Bandi, Syamala Mettetal, Jerome Manfredi, Mark Shyu, Wen-Chyi Donelan, Jill Chakravarty, Arijit |
author_facet | Hather, Gregory Liu, Ray Bandi, Syamala Mettetal, Jerome Manfredi, Mark Shyu, Wen-Chyi Donelan, Jill Chakravarty, Arijit |
author_sort | Hather, Gregory |
collection | PubMed |
description | Human tumor xenograft studies are the primary means to evaluate the biological activity of anticancer agents in late-stage preclinical drug discovery. The variability in the growth rate of human tumors established in mice and the small sample sizes make rigorous statistical analysis critical. The most commonly used summary of antitumor activity for these studies is the T/C ratio. However, alternative methods based on growth rate modeling can be used. Here, we describe a summary metric called the rate-based T/C, derived by fitting each animal’s tumor growth to a simple exponential model. The rate-based T/C uses all of the data, in contrast with the traditional T/C, which only uses a single measurement. We compare the rate-based T/C with the traditional T/C and assess their performance through a bootstrap analysis of 219 tumor xenograft studies. We find that the rate-based T/C requires fewer animals to achieve the same power as the traditional T/C. We also compare 14-day studies with 21-day studies and find that 14-day studies are more cost efficient. Finally, we perform a power analysis to determine an appropriate sample size. |
format | Online Article Text |
id | pubmed-4264612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-42646122015-01-08 Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies Hather, Gregory Liu, Ray Bandi, Syamala Mettetal, Jerome Manfredi, Mark Shyu, Wen-Chyi Donelan, Jill Chakravarty, Arijit Cancer Inform Review Human tumor xenograft studies are the primary means to evaluate the biological activity of anticancer agents in late-stage preclinical drug discovery. The variability in the growth rate of human tumors established in mice and the small sample sizes make rigorous statistical analysis critical. The most commonly used summary of antitumor activity for these studies is the T/C ratio. However, alternative methods based on growth rate modeling can be used. Here, we describe a summary metric called the rate-based T/C, derived by fitting each animal’s tumor growth to a simple exponential model. The rate-based T/C uses all of the data, in contrast with the traditional T/C, which only uses a single measurement. We compare the rate-based T/C with the traditional T/C and assess their performance through a bootstrap analysis of 219 tumor xenograft studies. We find that the rate-based T/C requires fewer animals to achieve the same power as the traditional T/C. We also compare 14-day studies with 21-day studies and find that 14-day studies are more cost efficient. Finally, we perform a power analysis to determine an appropriate sample size. Libertas Academica 2014-12-09 /pmc/articles/PMC4264612/ /pubmed/25574127 http://dx.doi.org/10.4137/CIN.S13974 Text en © 2014 the author(s), publisher and licensee Libertas Academica Ltd. This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 License. |
spellingShingle | Review Hather, Gregory Liu, Ray Bandi, Syamala Mettetal, Jerome Manfredi, Mark Shyu, Wen-Chyi Donelan, Jill Chakravarty, Arijit Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies |
title | Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies |
title_full | Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies |
title_fullStr | Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies |
title_full_unstemmed | Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies |
title_short | Growth Rate Analysis and Efficient Experimental Design for Tumor Xenograft Studies |
title_sort | growth rate analysis and efficient experimental design for tumor xenograft studies |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264612/ https://www.ncbi.nlm.nih.gov/pubmed/25574127 http://dx.doi.org/10.4137/CIN.S13974 |
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