Literature DB >> 26715775

Personalized biological treatment for rheumatoid arthritis: a systematic review with a focus on clinical applicability.

Bart V J Cuppen1, Paco M J Welsing2, Jan J Sprengers2, Johannes W J Bijlsma2, Anne C A Marijnissen2, Jacob M van Laar2, Floris P J G Lafeber2, Sandhya C Nair2.   

Abstract

OBJECTIVES: To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers.
METHODS: A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. The added value was determined by the added value on prior probability for each (bio)marker. Only an increase/decrease in chance of response ⩾15% was considered clinically relevant, whereas in oncology values >25% are common.
RESULTS: Of the 57 eligible studies, 14 (bio)markers were studied in more than one cohort and an overview of the added predictive value of each marker is presented. Of the replicated predictors, none consistently showed an increase/decrease in probability of response ⩾15%. However, positivity of RF and ACPA in case of rituximab and the presence of the TNF-α promoter 308 GG genotype for TNF inhibitor therapy were consistently predictive, yet low in added predictive value. Besides these, 65 (bio)markers studied once showed remarkably high (but not validated) predictive values.
CONCLUSION: We were unable to address clinically useful baseline (bio)markers for use in individually tailored treatment. Some predictors are consistently predictive, yet low in added predictive value, while several others are promising but await replication. The challenge now is to design studies to validate all explored and promising findings individually and in combination to make these (bio)markers relevant to clinical practice.
© The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  ACR; EULAR; TNF inhibitors; abatacept; anakinra; biologics; biomarkers; markers; prediction; response; rheumatoid arthritis; rituximab; tocilizumab; treatment

Mesh:

Substances:

Year:  2015        PMID: 26715775     DOI: 10.1093/rheumatology/kev421

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.580


  30 in total

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