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FRI0470 Modification of ‘the asas modification of the berlin algorithm’ in patients with chronic low back pain can be useful for primary care
  1. L. Van Hoeven1,2,
  2. J. Luime2,
  3. M. Hazes2,
  4. A. Weel1
  1. 1Rheumatology, Maasstad Hospital
  2. 2Rheumatology, Erasmus Medical Centre, Rotterdam, Netherlands


Background Recently the ASAS modification of the Berlin algorithm (ASAS algorithm) for diagnosing axial spondyloarthritis (aSpA) was published1. The entry criterion, chronic low back pain (CLBP), started before the age of 45, implies that all young patients with CLBP can be referred to the rheumatologist for further diagnostic work-up. Since CLBP is one of the most frequent complaints in primary care, referring all these patients is unfeasible due to high cost.

Objectives To assess the performance of the ASAS modification of the Berlin algorithm in an unselected CLBP population; the CAFASPA cohort. To assess whether incorporating the referral model of the CaFaSpA study in the ASAS algorithm, has added value for primary care2.

Methods Patients (18-45 yrs) with CLBP were identified from GP records by the ICPC code L03. Assessments included questionnaires, history, physical examination, HLA-B27, CRP, X-ray and MRI. ASpA was defined by the ASAS criteria. A modification was assessed by incorporating the CaFaSpA referral rule in the ASAS algorithm. Descriptive statistics were used to determine the performance both the ASAS algorithm and the CaFaSpA modification of the ASAS algorithm.

Results 364 patients participated in the CaFaSpA study. In total 86 (23%) were classified as aSpA. The performance of the ASAS algorithm was 73.2% (n=30) for the X-ray arm, 40.0% (n=12) for the arm having ≥4 SpA features or 2-3 features plus HLA-B27 and 100.0% (n=3) for having 0-1 features plus HLA-B27 and a positive MRI. The data of the CaFaSpA modification were respectively, 100.0%, 60.0% and 100.0% (Fig. 1).

Conclusions The ASAS algorithm, assessed in secondary care, can not be applied in an unselected CLBP population. Adding the CaFaSpA referral model improves the performance of the ASAS algorithm substantial, leading to useful and more cost-effective model, for daily practice in both primary and secondary care.


  1. vd Berg et al. Annals of the Rheumatic diseases, 2012.

  2. v Hoeven et al. Arthritis and Rheumatism 2010

Disclosure of Interest L. Van Hoeven: None Declared, J. Luime: None Declared, M. Hazes: None Declared, A. Weel Grant/research support from: Unrestricted grand from Abbott

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