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A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib
Poor study methodology leads to biased measurement of treatment effects in preclinical research. We used available sunitinib preclinical studies to evaluate relationships between study design and experimental tumor volume effect sizes. We identified published animal efficacy experiments where suniti...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4600817/ https://www.ncbi.nlm.nih.gov/pubmed/26460544 http://dx.doi.org/10.7554/eLife.08351 |
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author | Henderson, Valerie C Demko, Nadine Hakala, Amanda MacKinnon, Nathalie Federico, Carole A Fergusson, Dean Kimmelman, Jonathan |
author_facet | Henderson, Valerie C Demko, Nadine Hakala, Amanda MacKinnon, Nathalie Federico, Carole A Fergusson, Dean Kimmelman, Jonathan |
author_sort | Henderson, Valerie C |
collection | PubMed |
description | Poor study methodology leads to biased measurement of treatment effects in preclinical research. We used available sunitinib preclinical studies to evaluate relationships between study design and experimental tumor volume effect sizes. We identified published animal efficacy experiments where sunitinib monotherapy was tested for effects on tumor volume. Effect sizes were extracted alongside experimental design elements addressing threats to valid clinical inference. Reported use of practices to address internal validity threats was limited, with no experiments using blinded outcome assessment. Most malignancies were tested in one model only, raising concerns about external validity. We calculate a 45% overestimate of effect size across all malignancies due to potential publication bias. Pooled effect sizes for specific malignancies did not show apparent relationships with effect sizes in clinical trials, and we were unable to detect dose–response relationships. Design and reporting standards represent an opportunity for improving clinical inference. DOI: http://dx.doi.org/10.7554/eLife.08351.001 |
format | Online Article Text |
id | pubmed-4600817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-46008172015-10-14 A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib Henderson, Valerie C Demko, Nadine Hakala, Amanda MacKinnon, Nathalie Federico, Carole A Fergusson, Dean Kimmelman, Jonathan eLife Epidemiology and Global Health Poor study methodology leads to biased measurement of treatment effects in preclinical research. We used available sunitinib preclinical studies to evaluate relationships between study design and experimental tumor volume effect sizes. We identified published animal efficacy experiments where sunitinib monotherapy was tested for effects on tumor volume. Effect sizes were extracted alongside experimental design elements addressing threats to valid clinical inference. Reported use of practices to address internal validity threats was limited, with no experiments using blinded outcome assessment. Most malignancies were tested in one model only, raising concerns about external validity. We calculate a 45% overestimate of effect size across all malignancies due to potential publication bias. Pooled effect sizes for specific malignancies did not show apparent relationships with effect sizes in clinical trials, and we were unable to detect dose–response relationships. Design and reporting standards represent an opportunity for improving clinical inference. DOI: http://dx.doi.org/10.7554/eLife.08351.001 eLife Sciences Publications, Ltd 2015-10-13 /pmc/articles/PMC4600817/ /pubmed/26460544 http://dx.doi.org/10.7554/eLife.08351 Text en © 2015, Henderson et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Henderson, Valerie C Demko, Nadine Hakala, Amanda MacKinnon, Nathalie Federico, Carole A Fergusson, Dean Kimmelman, Jonathan A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
title | A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
title_full | A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
title_fullStr | A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
title_full_unstemmed | A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
title_short | A meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
title_sort | meta-analysis of threats to valid clinical inference in preclinical research of sunitinib |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4600817/ https://www.ncbi.nlm.nih.gov/pubmed/26460544 http://dx.doi.org/10.7554/eLife.08351 |
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