Literature DB >> 21088968

[Biomarkers collections: the future or a waste of resources?].

H-M Lorenz1.   

Abstract

Disease biomarkers would aim at a more specific definition of diagnosis or subtype of a certain disease, as well as prognosis definition, including efficacy and side effects of certain therapeutics. Biomarkers could lead to a prognostically optimized definition of remission in the individual patient and thus to a more objective definition of therapeutic efficacy. Is this possible and does it make sense? Or would an extensive analysis of biomarkers to date lead to a costly overestimation of as yet not well established biologic parameters? Although we are currently unable to answer this question, many colleagues argue in favour of more in depth research for a better evaluation of biomarkers in many diseases. This could save money if we were able to predict the efficacy of expensive drugs such as immunobiologics. Biomarkers comprise cytometric information, data on protein expression and secretion, mRNA, microRNA or DNA, including epigenetic variants. Although much of these data already exist in the scientific literature, it is associated with problems in terms of feasibility (for cytometry and RNA analysis only on-site analysis is possible, while for DNA analysis central testing is also possible), costs and reproducibility (ethnic variability!). To date all biomarkers have only limited value in terms of the above-mentioned aims. The present review compiles "PROs and CONs" in a subjective way in order to provoke a discussion on the meaningfulness of biomarkers, while at the same time supporting and encouraging further research in this field.

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Year:  2010        PMID: 21088968     DOI: 10.1007/s00393-010-0716-z

Source DB:  PubMed          Journal:  Z Rheumatol        ISSN: 0340-1855            Impact factor:   1.372


  3 in total

1.  A matrix risk model for the prediction of rapid radiographic progression in patients with rheumatoid arthritis receiving different dynamic treatment strategies: post hoc analyses from the BeSt study.

Authors:  K Visser; Y P M Goekoop-Ruiterman; J K de Vries-Bouwstra; H K Ronday; P E H Seys; P J S M Kerstens; T W J Huizinga; B A C Dijkmans; C F Allaart
Journal:  Ann Rheum Dis       Date:  2010-05-24       Impact factor: 19.103

Review 2.  A pilot risk model for the prediction of rapid radiographic progression in rheumatoid arthritis.

Authors:  Nathan Vastesaeger; Stephen Xu; Daniel Aletaha; E William St Clair; Josef S Smolen
Journal:  Rheumatology (Oxford)       Date:  2009-07-09       Impact factor: 7.580

3.  High anti-cyclic citrullinated peptide levels and an algorithm of four variables predict radiographic progression in patients with rheumatoid arthritis: results from a 10-year longitudinal study.

Authors:  S W Syversen; P I Gaarder; G L Goll; S Ødegård; E A Haavardsholm; P Mowinckel; D van der Heijde; R Landewé; T K Kvien
Journal:  Ann Rheum Dis       Date:  2007-05-25       Impact factor: 19.103

  3 in total
  1 in total

1.  Blood cell MicroRNAs and blood product safety.

Authors:  Somsri Wiwanitkit; Viroj Wiwanitkit
Journal:  Asian J Transfus Sci       Date:  2012-07
  1 in total

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