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Updated: Jun 15, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Successes achieved and challenges ahead in translating biomarkers into clinical applications
Greg Tesch1, Shashi Amur, John T Schousboe
1Department of Nephrology, Monash Medical Center, Clayton, Victoria, Australia.
Abstract:
Biomarkers are important tools for identifying and stratifying diseases, predicting their progression and determining the effectiveness, safety, and doses of therapeutic interventions. This is important for common chronic diseases such as diabetic nephropathy, osteoporosis, and rheumatoid arthritis which affect large numbers of patients worldwide. This article summarizes the current knowledge of established and novel biomarkers for each of these diseases as presented at the 2008 AAPS/ACCP joint symposium "Success Achieved and Challenges Ahead in Translating Biomarkers into Clinical Applications," in Atlanta, Georgia. The advantages and disadvantages of various proteomic, metabolomic, genomic, and imaging biomarkers are discussed in relation to disease diagnosis and stratification, prognosis, drug development, and potential clinical applications. The use of biomarkers as a means to determine therapeutic interventions is also considered. In addition, we show that biomarkers may be useful for adapting therapies for individual needs by allowing the selection of patients who are most likely to respond or react adversely to a particular treatment. They may also be used to determine whether the development of a novel therapy is worth pursuing by informing crucial go/no go decisions around safety and efficacy. Indeed, regulatory bodies now suggest that effective integration of biomarkers into clinical drug development programs is likely to promote the development of novel therapeutics and more personalized medicine.
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