Literature DB >> 21447279

Biomarkers for chronic pain and analgesia. Part 1: the need, reality, challenges, and solutions.

David Borsook1, Lino Becerra, Richard Hargreaves.   

Abstract

Chronic pain remains a significant clinical problem that has few effective therapies. Currently the success rate for treating chronic pain with analgesics is around 30%. Both treatment and research into chronic pain are greatly compromised by the fact that there is no objective diagnostic test that can complement the subjective assessment of chronic pain conditions. Chronic pain is now considered to be a disease of the central nervous system. Since behavior (including pain or analgesia) results from activity in brain circuits through the participation of many brain regions, we suggest that specific measures for the disease state and for drug effects can be defined using functional brain imaging. Tremendous advances have been made in functional imaging in the field of pain and analgesics and the development of CNS imaging biomarkers for pain may be close at hand. The successful identification of functional brain "signatures" for both drug action (analgesia) and disease state (neuropathic pain) when qualified could provide objective biomarkers to guide for drug development and clinical practice. In this two-part review, we discuss the potential of biomarkers for chronic pain including functional neuroimaging together with the challenges and limitations that are likely to be faced during the implementation of this strategy. The fit-for-purpose, scientific validation, and clinical qualification of novel CNS biomarkers for chronic pain could dramatically change the current outlook for treatment of chronic pain and research into its etiology.

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Year:  2011        PMID: 21447279

Source DB:  PubMed          Journal:  Discov Med        ISSN: 1539-6509            Impact factor:   2.970


  47 in total

Review 1.  Neurological diseases and pain.

Authors:  David Borsook
Journal:  Brain       Date:  2011-11-08       Impact factor: 13.501

Review 2.  Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

Authors:  Jeff Boissoneault; Landrew Sevel; Janelle Letzen; Michael Robinson; Roland Staud
Journal:  Curr Rheumatol Rep       Date:  2017-01       Impact factor: 4.592

Review 3.  Descending pain modulation and chronification of pain.

Authors:  Michael H Ossipov; Kozo Morimura; Frank Porreca
Journal:  Curr Opin Support Palliat Care       Date:  2014-06       Impact factor: 2.302

Review 4.  Chronic pain assessment from bench to bedside: lessons along the translation continuum.

Authors:  Bryan Jensen
Journal:  Transl Behav Med       Date:  2016-12       Impact factor: 3.046

Review 5.  The young brain and concussion: imaging as a biomarker for diagnosis and prognosis.

Authors:  Esteban Toledo; Alyssa Lebel; Lino Becerra; Anna Minster; Clas Linnman; Nasim Maleki; David W Dodick; David Borsook
Journal:  Neurosci Biobehav Rev       Date:  2012-03-28       Impact factor: 8.989

Review 6.  Lost but making progress--Where will new analgesic drugs come from?

Authors:  David Borsook; Richard Hargreaves; Chas Bountra; Frank Porreca
Journal:  Sci Transl Med       Date:  2014-08-13       Impact factor: 17.956

Review 7.  Migrainomics - identifying brain and genetic markers of migraine.

Authors:  Dale R Nyholt; David Borsook; Lyn R Griffiths
Journal:  Nat Rev Neurol       Date:  2017-11-17       Impact factor: 42.937

Review 8.  Positive emotions and brain reward circuits in chronic pain.

Authors:  Edita Navratilova; Kozo Morimura; Jennifer Y Xie; Christopher W Atcherley; Michael H Ossipov; Frank Porreca
Journal:  J Comp Neurol       Date:  2016-02-03       Impact factor: 3.215

9.  Test-retest reliability of pain-related brain activity in healthy controls undergoing experimental thermal pain.

Authors:  Janelle E Letzen; Landrew S Sevel; Charles W Gay; Andrew M O'Shea; Jason G Craggs; Donald D Price; Michael E Robinson
Journal:  J Pain       Date:  2014-07-03       Impact factor: 5.820

10.  The Effect of Base Rate on the Predictive Value of Brain Biomarkers.

Authors:  Michael Robinson; Jeff Boissoneault; Landrew Sevel; Janelle Letzen; Roland Staud
Journal:  J Pain       Date:  2016-04-08       Impact factor: 5.820

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