Predicting the severity of joint damage in rheumatoid arthritis; The contribution of genetic factors

Annals of the Rheumatic Diseases

Volumn 74, Issue 5, 2015, Pages 876-882

  Van Steenbergen, Hanna W ^a   Tsonaka, Roula ^a   Huizinga, Tom W J ^a   Le Cessie, Saskia ^a   Van Der Helm Van Mil, Annette H M ^a   Kvien, Tore K ^b  

^a LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

^b Medical Center ^*

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ADULT; ARTICLE; DISEASE COURSE; DISEASE SEVERITY; FEMALE; FOOT RADIOGRAPHY; GENETIC ASSOCIATION; GENETIC RISK; HAND RADIOGRAPHY; HUMAN; JOINT INJURY; MAJOR CLINICAL STUDY; MALE; OUTCOME ASSESSMENT; PATIENT CODING; PREDICTION; PRIORITY JOURNAL; RHEUMATOID ARTHRITIS; RISK FACTOR; SENSITIVITY ANALYSIS; X RAY; AGED; FOOT JOINT; GENETICS; HAND JOINT; MIDDLE AGED; RADIOGRAPHY; REGRESSION ANALYSIS; RETROSPECTIVE STUDY; SEVERITY OF ILLNESS INDEX; SINGLE NUCLEOTIDE POLYMORPHISM;

ADULT; AGED; ARTHRITIS, RHEUMATOID; DISEASE PROGRESSION; FEMALE; FOOT JOINTS; HAND JOINTS; HUMANS; MALE; MIDDLE AGED; POLYMORPHISM, SINGLE NUCLEOTIDE; REGRESSION ANALYSIS; RETROSPECTIVE STUDIES; SEVERITY OF ILLNESS INDEX;

EID: 84926628382     PISSN: 00034967     EISSN: 14682060     Source Type: Journal    
DOI: 10.1136/annrheumdis-2013-204277     Document Type: Article

References (28)

1. Odegard S, Landewe R, van der Heijde D, et al. Association of early radiographic damage with impaired physical function in rheumatoid arthritis: a ten-year, longitudinal observational study in 238 patients. Arthritis Rheum 2006;54: 68-75.
2. Knevel R, Grondal G, Huizinga TW, et al. Genetic predisposition of the severity of joint destruction in rheumatoid arthritis: a population-based study. Ann Rheum Dis 2012;71:707-9.
3. Knevel R, Krabben A, Wilson AG, et al. A genetic variant in granzyme B is associated with progression of joint destruction in rheumatoid arthritis. Arthritis Rheum 2013;65:582-9.
4. de Rooy DP, Yeremenko NG, Wilson AG, et al. Genetic studies on components of the Wnt signalling pathway and the severity of joint destruction in rheumatoid arthritis. Ann Rheum Dis 2013;72:769-75.
5. de Rooy DP, Zhernakova A, Tsonaka R, et al. A genetic variant in the region of MMP-9 is associated with serum levels and progression of joint damage in rheumatoid arthritis. Ann Rheum Dis 2014;73:1163-9.
6. Knevel R, Klein K, Somers K, et al. Identification of a genetic variant for joint damage progression in autoantibody-positive rheumatoid arthritis. Ann Rheum Dis 2014;73:2038-46.
7. de Rooy DP, van der Linden MP, Knevel R, et al. Predicting arthritis outcomes-what can be learned from the Leiden Early Arthritis Clinic? Rheumatology (Oxford) 2011;50:93-100.
8. Visser K, Goekoop-Ruiterman YP, de Vries-Bouwstra JK, et al. 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. Ann Rheum Dis 2010;69:1333-7.
9. Vastesaeger N, Xu S, Aletaha D, et al. A pilot risk model for the prediction of rapid radiographic progression in rheumatoid arthritis. Rheumatology (Oxford) 2009;48:1114-21.
10. Fautrel B, Granger B, Combe B, et al. Matrix to predict rapid radiographic progression of early rheumatoid arthritis patients from the community treated with methotrexate or leflunomide: results from the ESPOIR cohort. Arthritis Res Ther 2012;14:R249.
11. Syversen SW, Gaarder PI, Goll GL, et al. 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. Ann Rheum Dis 2008;67:212-17.
12. Lillegraven S, Paynter N, Prince FH, et al. Performance of matrix-based risk models for rapid radiographic progression in a cohort of patients with established rheumatoid arthritis. Arthritis Care Res (Hoboken) 2013;65:526-33.
13. Durnez A, Vanderschueren G, Lateur L, et al. Effectiveness of initial treatment allocation based on expert opinion for prevention of rapid radiographic progression in daily practice of an early RA cohort. Ann Rheum Dis 2011;70:634-7.
14. van Riel PLCM, Fransen J, Scott DL. Eular handbook of clinical assessments in rheumatoid arthritis. 2004. Alphen aan den Rijn, Van Zuiden Communications BV 2004:10-21.
15. van der Linden MP, Feitsma AL, le Cessie S, et al. Association of a single-nucleotide polymorphism in CD40 with the rate of joint destruction in rheumatoid arthritis. Arthritis Rheum 2009;60:2242-7.
16. Knevel R, Krabben A, Brouwer E, et al. Genetic variants in IL15 associate with progression of joint destruction in rheumatoid arthritis: a multicohort study. Ann Rheum Dis 2012;71:1651-7.
17. Krabben A, Wilson AG, de Rooy DP, et al. Brief report: Association of genetic variants in the IL4 and IL4R genes with the severity of joint damage in rheumatoid arthritis: a study in seven cohorts. Arthritis Rheum 2013;65:3051-7.
18. Knevel R, de Rooy DP, Zhernakova A, et al. Association of variants in IL2RA with progression of joint destruction in Rheumatoid Arthritis. Arthritis Rheum 2013;65:1684-93.
19. Teare MD, Knevel R, Morgan MD, et al. Allele-dose association of the C5orf30 rs26232 variant with joint damage in rheumatoid arthritis. Arthritis Rheum 2013;65:2555-61.
20. Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures. Ann Intern Med 2009;150:795-802.
21. Steyerberg EW, Vickers AJ, Cook NRG, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 2010;21:128-38.
22. Knevel R, Tsonaka R, le Cessie S, et al. Comparison of methodologies for analysing the progression of joint destruction in rheumatoid arthritis. Scand J Rheumatol 2013;42:182-9.
23. Harrell FE Jr. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York: Springer-Verlag, 2001:204.
24. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361-87.
25. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008;27:157-72.
26. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007;115:928-35.
27. van der Helm-van Mil AH, Toes RE, Huizinga TW. Genetic variants in the prediction of rheumatoid arthritis. Ann Rheum Dis 2010;69:1694-6.
28. van der Helm-van Mil AH, Huizinga TW, Schreuder GM, et al. An independent role of protective HLA class II alleles in rheumatoid arthritis severity and susceptibility. Arthritis Rheum 2005;52:2637-44.