Association of nociplastic and neuropathic pain components with the presence of residual symptoms in patients with axial spondyloarthritis receiving biological disease-modifying antirheumatic drugs

OBJECTIVE

To evaluate the association of nociplastic (NoP) and neuropathic pain (NP) components with residual symptoms in patients with radiographic axial spondyloarthritis (r-axSpA) receiving biological disease-modifying antirheumatic drugs (bDMARDs).

METHODS

78 patients with r-axSpA from the GErman SPondyloarthritis Inception Cohort receiving a bDMARD for at least 3 months were included in this analysis. The Widespread Pain Index (WPI) and the PainDETECT (PD) questionnaire were used to quantify the NoP and the NP components, respectively. Axial Spondyloarthritis Disease Activity Score (ASDAS) and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) were used as measures of residual symptoms. C reactive protein (CRP) was used as a measure of systemic inflammatory activity. Univariable and multivariable regression analyses of disease activity were performed. The regions of the WPI score and items of the PD score were used for cluster analyses.

RESULTS

Linear multivariable regression analysis showed that WPI and PD were independently associated with ASDAS (b=0.1, 95% CI 0.04 to 0.17, and b=0.05, 95% CI 0.02 to 0.08, respectively) and BASDAI (b=0.24, 95% CI 0.08 to 0.39, and b=0.17, 95% CI 0.1 to 0.25, respectively) in r-axSpA patients receiving stable treatment with bDMARDs. Furthermore, WPI and PD were found to be significantly associated with the presence of relevant residual symptoms as defined by BASDAI ≥4 (OR 1.93, 95% CI 1.09 to 4.15, and OR 1.32, 95% CI 1.04 to 1.85, respectively). The effects were present also in patients with normal level of CRP. Cluster analysis revealed three distinct pain distribution profiles and four specific sensory symptom constellations allowing differentiation of different pain subtypes.

CONCLUSION

Both NoP and NP components seem to be associated with residual symptoms in patients with r-axSpA receiving treatment with bDMARDs.

Treatment with tumour necrosis factor inhibitors is associated with a time-shifted retardation of radiographic spinal progression in patients with axial spondyloarthritis

OBJECTIVE

The objective of the current study was to analyse the association between treatment with tumour necrosis factor inhibitors (TNFi) and radiographic spinal progression in patients with axial spondyloarthritis (axSpA) from a long-term inception cohort.

METHODS

A total of 243 patients with axSpA from the German Spondyloarthritis Inception Cohort with at least two sets of spinal radiographs obtained at least 2 years apart during a 10-year follow-up were included. Spinal radiographs were evaluated by three trained and calibrated readers according to the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). The association between the current TNFi, previous TNFi and radiographic spinal progression defined as the absolute mSASSS change score over 2 years was analysed using longitudinal generalised estimating equations analysis.

RESULTS

TNFi treatment in the current 2-year interval was not associated with retardation of radiographic spinal progression (β=-0.02 (95% CI -0.37 to 0.34) and -0.17 (95% CI -0.54 to 0.20) for any and ≥12 months treatment duration, respectively, adjusted for sex, the Ankylosing Spondylitis Disease Activity Score, smoking, presence of definite radiographic sacroiliitis, mSASSS at baseline and non-steroidal anti-inflammatory drug intake). TNFi treatment in the previous 2-year interval, was, however, significantly associated with reduction of mSASSS progression, which was especially evident in patients who received TNFi in the previous and in the current intervals: β=-0.58 (95% CI -1.02 to -0.13), adjusted for the same variables.

CONCLUSION

TNFi treatment was associated with a time-shifted effect on radiographic spinal progression in axSpA that became evident between years 2 and 4 after treatment initiation.

Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance

BACKGROUND

Radiographs of the sacroiliac joints are commonly used for the diagnosis and classification of axial spondyloarthritis. The aim of this study was to develop and validate an artificial neural network for the detection of definite radiographic sacroiliitis as a manifestation of axial spondyloarthritis (axSpA).

METHODS

Conventional radiographs of the sacroiliac joints obtained in two independent studies of patients with axSpA were used. The first cohort comprised 1553 radiographs and was split into training (n = 1324) and validation (n = 229) sets. The second cohort comprised 458 radiographs and was used as an independent test dataset. All radiographs were assessed in a central reading session, and the final decision on the presence or absence of definite radiographic sacroiliitis was used as a reference. The performance of the neural network was evaluated by calculating areas under the receiver operating characteristic curves (AUCs) as well as sensitivity and specificity. Cohen's kappa and the absolute agreement were used to assess the agreement between the neural network and the human readers.

RESULTS

The neural network achieved an excellent performance in the detection of definite radiographic sacroiliitis with an AUC of 0.97 and 0.94 for the validation and test datasets, respectively. Sensitivity and specificity for the cut-off weighting both measurements equally were 88% and 95% for the validation and 92% and 81% for the test set. The Cohen's kappa between the neural network and the reference judgements were 0.79 and 0.72 for the validation and test sets with an absolute agreement of 90% and 88%, respectively.

CONCLUSION

Deep artificial neural networks enable the accurate detection of definite radiographic sacroiliitis relevant for the diagnosis and classification of axSpA.