title: Study designs and statistical analyses for biomarker research.
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.
authors.affiliation: Graduate School of Engineering, Tokyo University of Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-8601, Japan. robin_gosho@yahoo.co.jp
authors.forename: Masahiko
authors.initials: M
authors.lastname: Gosho
authors.forename: Kengo
authors.initials: K
authors.lastname: Nagashima
authors.forename: Yasunori
authors.initials: Y
authors.lastname: Sato
mesh_terms: D015415:Biomarkers / Q000378:metabolism*; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis / Q000378:metabolism; D057285:Precision Medicine; D011237:Predictive Value of Tests; D011379:Prognosis; D012107:Research Design
chemical_list: D015415:Biomarkers