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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...

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Autores principales: Hather, Gregory, Liu, Ray, Bandi, Syamala, Mettetal, Jerome, Manfredi, Mark, Shyu, Wen-Chyi, Donelan, Jill, Chakravarty, Arijit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2014
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.
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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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