https://scholars.lib.ntu.edu.tw/handle/123456789/520971
Title: | Predictive biomarkers for treatment selection: Statistical considerations | Authors: | Chen J.J. TZU-PIN LU Chen Y.-C. Lin W.-J. |
Issue Date: | 2015 | Publisher: | Future Medicine Ltd. | Journal Volume: | 9 | Journal Issue: | 11 | Start page/Pages: | 1121-1135 | Source: | Biomarkers in Medicine | Abstract: | Predictive biomarkers are developed for treatment selection to identify patients who are likely to benefit from a particular therapy. This review describes statistical methods and discusses issues in the development of predictive biomarkers to enhance study efficiency for detection of treatment effect on the selected responder patients in clinical studies. The statistical procedure for treatment selection consists of three components: biomarker identification, subgroup selection and clinical utility assessment. Major statistical issues discussed include biomarker designs, procedures to identify predictive biomarkers, classification models for subgroup selection, subgroup analysis and multiple testing for clinical utility assessment and evaluation. ? 2015 Future Medicine Ltd. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84947746952&doi=10.2217%2fbmm.15.84&partnerID=40&md5=4f9fcd221a29d3c7f949e4686066e221 https://scholars.lib.ntu.edu.tw/handle/123456789/520971 |
ISSN: | 1752-0363 | DOI: | 10.2217/bmm.15.84 | SDG/Keyword: | biological marker; biological marker; clinical assessment; clinical effectiveness; clinical evaluation; false discovery rate; human; mathematical analysis; mathematical computing; mathematical model; patient identification; patient selection; personalized medicine; pharmacodynamics; Review; risk assessment; statistical analysis; study design; treatment planning; biostatistics; decision making; procedures; safety; therapy; Biomarkers; Biostatistics; Decision Making; Humans; Safety; Therapeutics |
Appears in Collections: | 流行病學與預防醫學研究所 |
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