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Predicting the severity of joint damage in rheumatoid arthritis; the contribution of genetic factors
  1. Hanna W van Steenbergen1,
  2. Roula Tsonaka2,
  3. Tom WJ Huizinga1,
  4. Saskia le Cessie2,3,
  5. Annette HM van der Helm-van Mil1
  1. 1Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands
  2. 2Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
  3. 3Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
  1. Correspondence to HW van Steenbergen, Department of Rheumatology, Leiden University Medical Center, P.O. Box 9600, Leiden 2300 RC, The Netherlands; h.w.van_steenbergen{at}lumc.nl

Abstract

Background The severity of radiologic progression is variable between rheumatoid arthritis (RA) patients. Recently, several genetic severity variants have been identified and were replicated, these belong to 12 loci. This study determined the contribution of the identified genetic factors to the explained variance in radiologic progression and whether genetic factors, in addition to traditional risk factors, improve the accuracy of predicting the severity of radiologic progression.

Methods 426 early RA patients with yearly radiologic follow-up were studied. The main outcome measure was the progression in Sharp-van der Heijde score (SHS) over 6 years, assessed as continuous outcome or categorised in no/little, moderate or severe progression. Assessed were improved fit of a linear mixed model analysis on serial radiographs, R2 using linear regression analyses, C-statistic and the net proportion of patients that was additionally correctly classified when adding genetic risk factors to a model consisting of traditional risk factors.

Results The genetic factors together explained 12–18%. When added to a model including traditional factors and treatment effects, the genetic factors additionally explained 3–7% of the variance (p value R2change=0.056). The percentage of patients that was correctly classified increased from 56% to 62%; the net proportion of correct reclassifications 6% (95% CI 3 to 10%). The C-statistic increased from 0.78 to 0.82. Sensitivity analyses using imputation of missing radiographs yielded comparable results.

Conclusions Genetic risk factors together explained 12–18% of the variance in radiologic progression. Adding genetic factors improved the predictive accuracy, but 38% of the patients were still incorrectly classified, limiting the value for use in clinical practice.

  • Rheumatoid Arthritis
  • Gene Polymorphism
  • Disease Activity

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