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Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors

Information about tumors is usually obtained from a single assessment of a tumor sample, performed at some point in the course of the development and progression of the tumor, with patient characteristics being surrogates for natural history context. Differences between cells within individual tumor...

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Detalles Bibliográficos
Autores principales: Axelrod, David E., Miller, Naomi, Chapman, Judith-Anne W.
Formato: Texto
Lenguaje:English
Publicado: Libertas Academica 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2828739/
https://www.ncbi.nlm.nih.gov/pubmed/20191105
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author Axelrod, David E.
Miller, Naomi
Chapman, Judith-Anne W.
author_facet Axelrod, David E.
Miller, Naomi
Chapman, Judith-Anne W.
author_sort Axelrod, David E.
collection PubMed
description Information about tumors is usually obtained from a single assessment of a tumor sample, performed at some point in the course of the development and progression of the tumor, with patient characteristics being surrogates for natural history context. Differences between cells within individual tumors (intratumor heterogeneity) and between tumors of different patients (intertumor heterogeneity) may mean that a small sample is not representative of the tumor as a whole, particularly for solid tumors which are the focus of this paper. This issue is of increasing importance as high-throughput technologies generate large multi-feature data sets in the areas of genomics, proteomics, and image analysis. Three potential pitfalls in statistical analysis are discussed (sampling, cut-points, and validation) and suggestions are made about how to avoid these pitfalls.
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spelling pubmed-28287392010-02-25 Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors Axelrod, David E. Miller, Naomi Chapman, Judith-Anne W. Biomed Inform Insights Review Information about tumors is usually obtained from a single assessment of a tumor sample, performed at some point in the course of the development and progression of the tumor, with patient characteristics being surrogates for natural history context. Differences between cells within individual tumors (intratumor heterogeneity) and between tumors of different patients (intertumor heterogeneity) may mean that a small sample is not representative of the tumor as a whole, particularly for solid tumors which are the focus of this paper. This issue is of increasing importance as high-throughput technologies generate large multi-feature data sets in the areas of genomics, proteomics, and image analysis. Three potential pitfalls in statistical analysis are discussed (sampling, cut-points, and validation) and suggestions are made about how to avoid these pitfalls. Libertas Academica 2009-03-30 /pmc/articles/PMC2828739/ /pubmed/20191105 Text en © 2009 the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article published under the Creative Commons CC-BY-NC 3.0 license.
spellingShingle Review
Axelrod, David E.
Miller, Naomi
Chapman, Judith-Anne W.
Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
title Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
title_full Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
title_fullStr Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
title_full_unstemmed Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
title_short Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
title_sort avoiding pitfalls in the statistical analysis of heterogeneous tumors
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2828739/
https://www.ncbi.nlm.nih.gov/pubmed/20191105
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