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Study Designs and Statistical Analyses for Biomarker Research
Graduate School of Engineering, Tokyo University of Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-8601, Japan
Faculty of Pharmaceutical Sciences, Josai University, 1-1 Keyakidai, Sakado-shi, Saitama 350-0295, Japan
Clinical Research Center, Chiba University of Medicine, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan
* Author to whom correspondence should be addressed.
Received: 15 May 2012; in revised form: 21 June 2012 / Accepted: 21 June 2012 / Published: 29 June 2012
Abstract: 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.
Keywords: biomarker adaptive design; confounding; multiplicity; predictive factor; statistical test
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Cite This Article
MDPI and ACS Style
Gosho, M.; Nagashima, K.; Sato, Y. Study Designs and Statistical Analyses for Biomarker Research. Sensors 2012, 12, 8966-8986.
Gosho M, Nagashima K, Sato Y. Study Designs and Statistical Analyses for Biomarker Research. Sensors. 2012; 12(7):8966-8986.
Gosho, Masahiko; Nagashima, Kengo; Sato, Yasunori. 2012. "Study Designs and Statistical Analyses for Biomarker Research." Sensors 12, no. 7: 8966-8986.