Journal Information
Vol. 7. Issue 2.
Pages 141-144 (March - April 2011)
Share
Share
Download PDF
More article options
Vol. 7. Issue 2.
Pages 141-144 (March - April 2011)
Continuing medical education
Full text access
Predictors of response to biologic therapies in rheumatoid arthritis
Factores predictores de respuesta a terapias biológicas en la artritis reumatoide
Visits
5144
Lara M. Chaves Chaparro
Corresponding author
chch@hotmail.com

Corresponding author.
, Juan Salvatierra Ossorio, Enrique Raya Álvarez
Servicio de Reumatología, Hospital Clínico San Cecilio, Granada, Spain
This item has received
Article information
Abstract

The advent of biological therapies has revolutionized the management of rheumatoid arthritis, demonstrating effectiveness in controlling clinical and radiological damage. However, 20% to 40% of the patients will not respond to these therapies, which are associated to a very high cost. In addition, non-responder patients are exposed to possible adverse effects. For these reasons, we need to identify predictors of response to these treatments. These predictors are reviewed in this evidence-based paper and classified into genetic and nongenetic. Despite extensive search, nowadays there are no predictors powerful enough to be used in regular clinical practice. Serum factors, the presence of rheumatoid factor and anti-cyclic citrullinated peptide antibodies, are the only factors currently being used to predict the response to specific biological therapy. In the future, probably thanks to new technologies based on genomics, transcriptomics and proteomics, it will be possible to identify genetic predictors of response to biological drugs that will allow us to select suitable patients for a specific biological therapy.

Keywords:
Biologic therapies
Rheumatoid arthritis
Response predictors
Resumen

El desarrollo de las terapias biológicas ha supuesto un gran avance en el manejo de la artritis reumatoide (AR) al haber demostrado efectividad en el control de la clínica y daño radiológico. Sin embargo, entre un 20–40% de los pacientes no van a responder a estas terapias, lo que determina un alto coste económico a la vez que los expone a posibles efectos adversos, por lo que se precisa de la identificación de factores predictores de respuesta a ellos. Estos se revisan en el actual trabajo en función de su evidencia científica y se clasifican en genéticos y no genéticos. A pesar de su extensa búsqueda, en la actualidad no disponemos de potentes predictores que puedan ser utilizados en la práctica clínica diaria. Posiblemente a día de hoy sólo los factores séricos, positividad del factor reumatoide (FR) y anticuerpos antipéptido citrulinado (anti-CCP) permiten predecir la respuesta a determinados biológicos. En un futuro, probablemente gracias a las nuevas tecnologías basadas en la genómica, transcriptómica y proteómica se identificarán predictores genéticos que permita seleccionar pacientes idóneos para una determinada terapia biológica.

Palabras clave:
Terapias biológicas
Artritis reumatoide
Predictores de respuesta
Full text is only aviable in PDF
References
[1.]
C. Bansard, T. Lequerré, M. Daveau, O. Boyer, F. Tron, J.P. Salier, et al.
Can rheumatoid arthritis responsiveness to methotrexate and biologics be predicted?.
Rheumatology, 48 (2009), pp. 1021-1028
[2.]
K.L. Hyrich, K.D. Watson, A.J. Silman, D.P.M. Symmons.
The BSR Biologics Register. Predictors of response to anti-TNF-a therapy among patients with rheumatoid arthritis: results from the British Society for Rhematology Biologics Register.
Rheumatology, 45 (2006), pp. 1558-1565
[4.]
C. Potter, K.L. Hyrich, A. Tracey, M. Lunt, D. Plant, D.P.M. Symmons, et al.
Association of rheumatoid factor and anti-cyclic citrullinated peptide positivity, but not carriage of shared epitope or PTPN22 susceptibility variants, with anti-tumour necrosis factor response in rheumatoid arthritis.
Ann Rheum Dis, 68 (2009), pp. 69-74
[5.]
F. Bobbio, R. Caporali, C. Alpini, S. Avalle, O.M. Epis, C. Klersy, et al.
High IgA rheumatoid factor levels are associated with poor clinical response to tumor necrosis factor inhibitors in rheumatoid arthritis.
Ann Rheum Dis, 66 (2007), pp. 302C-307C
[6.]
Y. Braun, D. Markovits, O. Zinder, D. Schapira, A. Rozin, M. Ehrenburg, et al.
Anti-cyclic citrullinated protein antibodies as predictor of response to anti-tumor necrosis factor-alpha therapy in patients with rheumatoid arthritis.
J Rheumatol, 33 (2006), pp. 497-500
[7.]
S. Fabre, A.M. Dupuy, N. Dossat, C. Guisset, J.D. Cohen, J.P. Cristol, et al.
Protein biochip array technology for cytokine profiling predicts etanercept responsiveness in rheumatoid arthritis.
Clin Exp Immunol, 253 (2008), pp. 188-195
[8.]
G. Morozzi, M. Fabbroni, F. Bellisai, S. Cucini, A. Simpatico, M. Galeazzi.
Low serum level of COMP, a cartilage turnover marker, predicts rapid and high ACR70 response to adalimumab therapy in rheumatoid arthritis.
Clin Rheumatol, 26 (2007), pp. 1335-1338
[9.]
R. Klaasen, R.M. Thurlings, C.A. Wiibrandts, A.W. Van Kuijk, D. Baeten, D.M. Gerlag, et al.
The relationship between synovial lymphocyte aggregates and the clinical response to infliximab in rheumatoid arthritis: a prospective study.
Arthritis Rheum, 60 (2009), pp. 3217-3224
[10.]
L. Padyukow, J. Lampa, M. Heimburger, S. Ernestams, T. Cederholm, I. LundKvist, et al.
Genetic markers for the efficacy of tumour necrosis factor blocking theraphy in rheumatoid arthritis.
Ann Rheum Dis, 62 (2003), pp. 526-529
[11.]
T.A. Manolio.
Genowide association studies and assessment of the risk of disease.
N Engl J Med, 363 (2010), pp. 166-176
[12.]
C. Liu, F. Batliwalla, W. Li, A. Lee, R. Roubenoff, E. Beckman, et al.
Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-tnf treatment in rheumatoid arthritis.
Mol Med., 14 (2008), pp. 575-578
[13.]
Y.H. Lee, J.D. Ji, S.C. Bae, G.G. Song.
Associations between tumor necrosis factor- a (TNF-a) -308. and -238 G/A polymorphisms and shared epitope status and responsiveness to TNF-a blockers in rheumatoid arthritis: a metaanalysis update.
J Rheumatol, 37 (2010), pp. 740-746
[14.]
M.J. Coenen, E.J. Toonen, H. Scheffer, T.R. Radstake, P. Barrera, B. Franke.
Pharmacogenetics of anti-TNF treatment in patients with rheumatoid arthritis.
Pharmacogenomics, 8 (2007), pp. 761-773
[15.]
A. Julià, A. Erra, C. Palacio, C. Tomas, X. Sans, P. Barceló, et al.
An eight-gene blood expression profile predicts the response to infliximab in rheumatoid arthritis.
[16.]
A. Julià, M. Barceló, A. Erra, C. Palacio, S. Marsal.
Identification of candidate genes for rituximab response in rheumatoid arthritis patients by microarray expression profiling blood cells.
Pharmacogenomics, 10 (2009), pp. 1297-1308
Copyright © 2011. Sociedad Española de Reumatología and Colegio Mexicano de Reumatología
Idiomas
Reumatología Clínica (English Edition)
Article options
Tools
es en

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?