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Estimation of renal cell carcinoma treatment effects from disease progression modeling
To improve future drug development efficiency in renal cell carcinoma (RCC), a disease progression model was developed with longitudinal tumor size data from a phase III trial of sorafenib in RCC. The best fit model was externally evaluated on 145 placebo-treated patients in a phase III trial of paz...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3791430/ https://www.ncbi.nlm.nih.gov/pubmed/23443753 http://dx.doi.org/10.1038/clpt.2012.263 |
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author | Maitland, Michael L. Wu, Kehua Sharma, Manish R. Jin, Yuyan Kang, Soonmo Peter Stadler, Walter M. Karrison, Theodore G. Ratain, Mark J. Bies, Robert R. |
author_facet | Maitland, Michael L. Wu, Kehua Sharma, Manish R. Jin, Yuyan Kang, Soonmo Peter Stadler, Walter M. Karrison, Theodore G. Ratain, Mark J. Bies, Robert R. |
author_sort | Maitland, Michael L. |
collection | PubMed |
description | To improve future drug development efficiency in renal cell carcinoma (RCC), a disease progression model was developed with longitudinal tumor size data from a phase III trial of sorafenib in RCC. The best fit model was externally evaluated on 145 placebo-treated patients in a phase III trial of pazopanib, and incorporated baseline tumor size, a linear disease progression component, and an exponential drug effect parameter. With the model-estimated effect of sorafenib on RCC growth we calculated the power of randomized phase II trials between sorafenib and hypothetical comparators over a range of effects. A hypothetical comparator with 80% greater drug effect than sorafenib would have 82% power (one-sided α = 0.1) with 50 patients per arm. Model-based quantitation of treatment effect with CT imaging offers a scaffold on which to develop new, more efficient, phase II trial endpoints and analytic strategies for RCC. |
format | Online Article Text |
id | pubmed-3791430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
record_format | MEDLINE/PubMed |
spelling | pubmed-37914302013-10-07 Estimation of renal cell carcinoma treatment effects from disease progression modeling Maitland, Michael L. Wu, Kehua Sharma, Manish R. Jin, Yuyan Kang, Soonmo Peter Stadler, Walter M. Karrison, Theodore G. Ratain, Mark J. Bies, Robert R. Clin Pharmacol Ther Article To improve future drug development efficiency in renal cell carcinoma (RCC), a disease progression model was developed with longitudinal tumor size data from a phase III trial of sorafenib in RCC. The best fit model was externally evaluated on 145 placebo-treated patients in a phase III trial of pazopanib, and incorporated baseline tumor size, a linear disease progression component, and an exponential drug effect parameter. With the model-estimated effect of sorafenib on RCC growth we calculated the power of randomized phase II trials between sorafenib and hypothetical comparators over a range of effects. A hypothetical comparator with 80% greater drug effect than sorafenib would have 82% power (one-sided α = 0.1) with 50 patients per arm. Model-based quantitation of treatment effect with CT imaging offers a scaffold on which to develop new, more efficient, phase II trial endpoints and analytic strategies for RCC. 2012-12-27 2013-04 /pmc/articles/PMC3791430/ /pubmed/23443753 http://dx.doi.org/10.1038/clpt.2012.263 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Maitland, Michael L. Wu, Kehua Sharma, Manish R. Jin, Yuyan Kang, Soonmo Peter Stadler, Walter M. Karrison, Theodore G. Ratain, Mark J. Bies, Robert R. Estimation of renal cell carcinoma treatment effects from disease progression modeling |
title | Estimation of renal cell carcinoma treatment effects from disease progression modeling |
title_full | Estimation of renal cell carcinoma treatment effects from disease progression modeling |
title_fullStr | Estimation of renal cell carcinoma treatment effects from disease progression modeling |
title_full_unstemmed | Estimation of renal cell carcinoma treatment effects from disease progression modeling |
title_short | Estimation of renal cell carcinoma treatment effects from disease progression modeling |
title_sort | estimation of renal cell carcinoma treatment effects from disease progression modeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3791430/ https://www.ncbi.nlm.nih.gov/pubmed/23443753 http://dx.doi.org/10.1038/clpt.2012.263 |
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