Performance of clinical, laboratory and imaging features for diagnosing spondyloarthritis-a systematic literature review and meta-analysis

Objective: The Berlin algorithm was developed to help diagnose axial SpA (axSpA), but new studies suggest some features typical of SpA are less specific than previously assumed. Furthermore, evidence is lacking for other SpA subtypes (e.g. peripheral SpA). We aimed to review the evidence on the performance of SpA features for diagnosing each SpA subtype.

Methods: We conducted a systematic literature review of studies reporting the diagnostic performance of one or more SpA features in patients with suspected SpA. The external reference was the rheumatologist's diagnosis of SpA. Meta-analysis was performed, separately for each SpA subtype, to estimate pooled sensitivity, specificity and positive and negative likelihood ratios (LR+ and LR-, respectively). Meta-regression assessed the effect of covariates (e.g. feature's prevalence) on each feature's performance.

Results: Of 13 844 articles screened, 46 were included. Sacroiliitis on MRI, damage on pelvic radiographs and elevated CRP had the best balance between LR+ and LR- (LR+ 3.9-17.0, LR- 0.5-0.7) for diagnosing axSpA. HLA-B27 had an LR+ lower than anticipated (LR+ 3.1). Inflammatory back pain (IBP) had a low LR+ (LR+ ≈1), but substantially decreased the likelihood of axSpA when absent (LR- 0.3). Conversely, peripheral features and extramusculoskeletal manifestations showed a high LR+ (LR+ 1.6-5.0), but were as common in axSpA as non-axSpA (LR- ≈1). The specificity of most features was reduced in settings when these were highly prevalent. Limited data precluded a detailed analysis on diagnosing other SpA subtypes.

Conclusion: Imaging features and CRP have good diagnostic value for axSpA. However, the specificity of other features, especially HLA-B27 and IBP, is lower than previously known.