Study Designs and Statistical Analyses for Biomarker Research

Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important...

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Detalles Bibliográficos
Autores principales: Gosho, Masahiko, Nagashima, Kengo, Sato, Yasunori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444086/
https://www.ncbi.nlm.nih.gov/pubmed/23012528
http://dx.doi.org/10.3390/s120708966
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author Gosho, Masahiko
Nagashima, Kengo
Sato, Yasunori
author_facet Gosho, Masahiko
Nagashima, Kengo
Sato, Yasunori
author_sort Gosho, Masahiko
collection PubMed
description Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research.
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spelling pubmed-34440862012-09-25 Study Designs and Statistical Analyses for Biomarker Research Gosho, Masahiko Nagashima, Kengo Sato, Yasunori Sensors (Basel) Review Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research. Molecular Diversity Preservation International (MDPI) 2012-06-29 /pmc/articles/PMC3444086/ /pubmed/23012528 http://dx.doi.org/10.3390/s120708966 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Review
Gosho, Masahiko
Nagashima, Kengo
Sato, Yasunori
Study Designs and Statistical Analyses for Biomarker Research
title Study Designs and Statistical Analyses for Biomarker Research
title_full Study Designs and Statistical Analyses for Biomarker Research
title_fullStr Study Designs and Statistical Analyses for Biomarker Research
title_full_unstemmed Study Designs and Statistical Analyses for Biomarker Research
title_short Study Designs and Statistical Analyses for Biomarker Research
title_sort study designs and statistical analyses for biomarker research
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444086/
https://www.ncbi.nlm.nih.gov/pubmed/23012528
http://dx.doi.org/10.3390/s120708966
work_keys_str_mv AT goshomasahiko studydesignsandstatisticalanalysesforbiomarkerresearch
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AT satoyasunori studydesignsandstatisticalanalysesforbiomarkerresearch

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