Identifying axial spondyloarthritis in Dutch primary care patients, ages 20-45 years, with chronic low back pain

Arthritis Care Res (Hoboken). 2014 Mar;66(3):446-53. doi: 10.1002/acr.22180.


Objective: To identify axial spondyloarthritis (SpA) in Dutch primary care patients with chronic low back pain (CLBP), and to design a simple referral model for general practitioners (GPs) that would identify patients at risk for axial SpA.

Methods: Patients (ages 20-45 years) with CLBP were identified from GP records. Assessments included inflammatory back pain questionnaires, medical interviews, physical examinations, HLA-B27, C-reactive protein level, conventional radiography, and magnetic resonance imaging. The outcome measure was axial SpA defined by the Assessment of SpondyloArthritis international Society (ASAS) criteria. Multivariable regression analysis with bootstrapping was used to develop the referral model.

Results: A total of 364 patients (mean ± SD age 36.3 ± 6.8 years) was recruited with a median symptom duration of 9.0 years. Eighty-six patients (24%) fulfilled the ASAS criteria for axial SpA. Of all potential determinants, the ASAS inflammatory back pain questionnaire, good response to nonsteroidal antiinflammatory drugs, family history of SpA, and symptom duration were identified as most relevant for diagnosing axial SpA by multivariable regression analysis related to axial SpA. The shrunken regression coefficients were, respectively, 1.04, 0.83, 0.73, and 0.23. The combination of these 4 items proved a useful area under the receiver operating characteristic curve of 0.75 (SE 0.03). In a simplified score model, at the suggested cutoff value of 1.5, the sensitivity was 83% and specificity was 59%.

Conclusion: This study shows that 1 of 4 primary care patients with CLBP was classified as having axial SpA. A preselection in primary care based on a combination of clinical items may be useful to facilitate the identification of patients at risk of axial SpA.

Publication types

  • Clinical Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms
  • Chronic Disease
  • Female
  • Humans
  • Logistic Models
  • Low Back Pain / epidemiology*
  • Low Back Pain / etiology
  • Male
  • Middle Aged
  • Netherlands / epidemiology
  • Prevalence
  • Primary Health Care / methods*
  • Spondylarthritis / complications
  • Spondylarthritis / diagnosis
  • Spondylarthritis / epidemiology*
  • Young Adult