Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Biochemical Markers of Bone Turnover and Their Role in Osteoporosis Diagnosis: A Narrative Review Publisher Pubmed



Khashayar P1, 2, 3 ; Meybodi HA2 ; Amoabediny G4, 5 ; Larijani B6
Authors
Show Affiliations
Authors Affiliations
  1. 1. Nanobiotechnalogy Department, University of Tehran, Tehran, Iran
  2. 2. Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Center for Microsystems Technology (CMST), Imec and Ghent University, Technologiepark, Ghent, Belgium
  4. 4. Department of Biotechnology, School of Engineering, University of Tehran, Tehran, Iran
  5. 5. Nanobiotechnology Department, Research Center for New Technology in Life Sciences Engineering, University of Tehran, Tehran, Iran
  6. 6. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

Source: Recent Patents on Endocrine# Metabolic and Immune Drug Discovery Published:2015


Abstract

Osteoporosis diagnosis, which is nowadays generaly made based on bone mineral density (BMD) measurements, suffers from certain limitations. Thus it is believed that bone turnover markers (BTMs) can help improve osteoporosis detection. The shifting interest toward this topic made us perform a review to gather information on existing markers and their role in osteoporosis diagnosis. Based on the results, in this review, a list of existing markers and some of their characteristics is provided. Moreover, a brief explanation of different types of variability met while using these markers is also described. Finally some of the patents provided for the diagnosis of these markers are presented. While the use of BTMs in osteoporosis diagnosis has certain advantages over BMD and clinical risk assessment tools, more studies are needed before they can be used as a separate tool in this regard. It could be concluded that despite the fact that BTMs are better than BMD not only in monitoring treatment but also in identifying those at-risk, the diagnostic value of BTMs in predicting osteoporosis is low, and thus a model is needed to assess several BTMs at the same time with higher accuracy and lower variability to overcome this limitation. © 2015 Bentham Science Publishers.