Site-specific assessment of spinal radiographic progression improves detection of TNF blocker-associated disease modification in axial spondyloarthritis: longitudinal observational data from the Swiss Clinical Quality Management Registry.

OBJECTIVES: To analyse whether time-varying treatment with tumour necrosis factor inhibitors (TNFi) in radiographic axial spondyloarthritis (r-axSpA) has a differential impact on structural damage progression on different spinal segments (cervical versus lumbar spine). METHODS: Patients with r-axSpA in the Swiss Clinical Quality Management cohort were included if cervical and lumbar radiographs were available at intervals of 2 years for a maximum of 10 years. Paired radiographs were scored by two calibrated readers according to the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). The relationship between TNFi use and progression in the cervical and the lumbar spine was analysed using generalised estimating equation models and adjustment for potential confounding. Radiographic progression per spinal segment was defined as an increase of ≥ 1 mSASSS unit or by the formation of ≥ 1 new syndesmophyte over 2 years. RESULTS: Mean ± SD symptom duration was 13.8 ± 9.8 years. Mean ± SD mSASSS progression per radiographic interval was 0.41 ± 1.69 units in the cervical spine and 0.45 ± 1.45 units in the lumbar spine (p = 0.66). Prior use of TNFi significantly reduced the odds of progression in the cervical spine by 68% (OR 0.32, 95% CI 0.14-0.72), but not in the lumbar spine (OR 0.99, 95% CI 0.52-1.88). A more restricted inhibition of progression in the lumbar spine was confirmed after multiple imputation of missing covariate data (OR 0.43, 95% CI 0.24-0.77 and 0.85, 95% CI 0.51-1.41, for the cervical and lumbar spine, respectively). It was also confirmed with progression defined as formation of ≥ 1 syndesmophyte (OR 0.31, 95% CI 0.12-0.80 versus OR 0.56, 95% CI 0.26-1.24 for the cervical and lumbar spine, respectively). CONCLUSION: Disease modification by treatment with TNFi seems to more profoundly affect the cervical spine in this r-axSpA population with longstanding disease. Site-specific analysis of spinal progression might, therefore, improve detection of disease modification in clinical trials in axSpA.

Corrigendum: Computed tomography-based assessment of radiographic progression in spine and sacroiliac joints after pregnancy in women with radiographic axial spondyloarthritis.

[This corrects the article DOI: 10.3389/fmed.2022.970546.].

Prediction of radiographic progression pattern in patients with ankylosing spondylitis using group-based trajectory modeling and decision trees.

Objective: This study aimed to identify trajectories of radiographic progression of the spine over time and use them, along with associated clinical factors, to develop a prediction model for patients with ankylosing spondylitis (AS). Methods: Data from the medical records of patients diagnosed with AS in a single center were extracted between 2001 and 2018. Modified Stoke Ankylosing Spondylitis Spinal Scores (mSASSS) were estimated from cervical and lumbar radiographs. Group-based trajectory modeling classified patients into trajectory subgroups using longitudinal mSASSS data. In multivariate analysis, significant clinical factors associated with trajectories were selected and used to develop a decision tree for prediction of radiographic progression. The most appropriate group for each patient was then predicted using decision tree analysis. Results: We identified three trajectory classes: class 1 had a uniformly increasing slope of mSASSS, class 2 showed sustained low mSASSS, and class 3 showed little change in the slope of mSASSS but highest mSASSS from time of diagnosis to after progression. In multivariate analysis for predictive factors, female sex, younger age at diagnosis, lack of eye involvement, presence of peripheral joint involvement, and low baseline erythrocyte sedimentation rate (log) were significantly associated with class 2. Class 3 was significantly associated with male sex, older age at diagnosis, presence of ocular involvement, and lack of peripheral joint involvement when compared with class 1. Six clinical factors from multivariate analysis were used for the decision tree for classifying patients into three trajectories of radiographic progression. Conclusion: We identified three patterns of radiographic progression over time and developed a decision tree based on clinical factors to classify patients according to their trajectories of radiographic progression. Clinically, this model holds promise for predicting prognosis in patients with AS.

A pilot study on deep learning-based grading of corners of vertebral bodies for assessment of radiographic progression in patients with ankylosing spondylitis.

Background: Radiographs are widely used to evaluate radiographic progression with modified stoke ankylosing spondylitis spinal score (mSASSS). Objective: This pilot study aimed to develop a deep learning model for grading the corners of the cervical and lumbar vertebral bodies for computer-aided detection of mSASSS in patients with ankylosing spondylitis (AS). Methods: Digital radiographic examination of the spine was performed using Discovery XR656 (GE Healthcare) and Digital Diagnost (Philips). The disk points were detected between the bodies using a key-point detection deep learning model from the image obtained in DICOM (digital imaging and communications in medicine) format from the cervical and lumbar spinal radiographs. After cropping the vertebral regions around the disk point, the lower and upper corners of the vertebral bodies were classified as grade 3 (total bony bridges) or grades 0, 1, or 2 (non-bridges). We trained a convolutional neural network model to predict the grades in the lower and upper corners of the vertebral bodies. The performance of the model was evaluated in a validation set, which was separate from the training set. Results: Among 1280 patients with AS for whom mSASSS data were available, 5,083 cervical and 5245 lumbar lateral radiographs were reviewed. The total number of corners where mSASSS was measured in the cervical and lumbar vertebrae, including the upper and lower corners, was 119,414. Among them, the number of corners in the training and validation sets was 110,088 and 9326, respectively. The mean accuracy, sensitivity, and specificity for mSASSS scoring in one corner of the vertebral body were 0.91604, 0.80288, and 0.94244, respectively. Conclusion: A high-performance deep learning model for grading the corners of the vertebral bodies was developed for the first time. This model must be improved and further validated to develop a computer-aided tool for assessing mSASSS in the future.

Computed tomography-based assessment of radiographic progression in spine and sacroiliac joints after pregnancy in women with radiographic axial spondyloarthritis.

Background: Mechanical stress are one of the pathogenesis of axial spondyloarthritis (axSpA). During pregnancy, the mechanical overload on the spine and pelvis increases due to gravid uterus. We aimed to investigate whether pregnancy affects radiographic progression in patients with radiographic axSpA (r-axSpA) based on computed tomography (CT) evaluations. Materials and methods: This retrospective study included women with r-axSpA aged 19-49 years who underwent at least two CT evaluations of the whole spine and/or sacroiliac joints (SIJs) at intervals of 2-4 years. To compare radiographic progression after delivery, we classified the patients into two groups: delivery group and controls. The delivery group was restricted to women who had the first CT ∼2 years before delivery and the second CT ∼2 years after delivery. The CT Syndesmophyte Score (CTSS) (0-522) and SIJ scores (0-40) were used to evaluate spinal syndesmophytes and erosion, joint space narrowing, and sclerosis of the SIJs. Results: A total of 21 women in the delivery group and 38 women in the control group were included. The median (Q1-Q3) CTSS at baseline in the delivery group and controls was 19 (16-23) and 20 (13.25-27.75), and the median progression was 1 (0-3) and 0 (0-1) during the median 2.9-year follow-up, respectively. The median (Q1-Q3) SIJ score at baseline in the delivery group and controls was 13 (8-22) and 11 (6-22), and the median progression was 1.5 (0-3) and 1 (0-2), respectively. Using cut-off 0.5, 52.9, and 61.9% of r-axSpA patients and 39.3 and 44.4% of controls showed progression of whole spine and SIJs, respectively. However, no difference in proportion of spinal and SIJ progression and absolute score changes per time point was observed between two groups. Moreover, the SIJ score changes were comparable according to the delivery method. Conclusion: Pregnancy and delivery do not affect the radiographic progression of the spine and SIJs in women with r-axSpA assessed by CT.

Health assessment questionnaire-disability index (HAQ-DI) score at the start of biological disease-modifying antirheumatic drug (bDMARD) therapy is associated with radiographic progression of large joint damage in patients with rheumatoid arthritis.

OBJECTIVES: Radiographic progression of damage (RPD) to large joints in patients with rheumatoid arthritis (RA) has not been fully studied. We previously demonstrated that Larsen grade of the large joints was associated with RPD of large joints in patients treated with biological disease-modifying anti-rheumatic drugs (bDMARDs); however, no factors associated with background characteristics of patients were identified. METHODS: A total of 400 large joints in the upper and lower extremities, including the shoulder, elbow, knee, and ankle, of 88 patients with RA treated with bDMARDs for 1-3 years were investigated. Radiographs of tender and/or swollen large joints were acquired at least twice during the study period (mean, 16.4 months), and the RPD was evaluated. RESULTS: A multivariate analysis revealed that health assessment questionnaire-disability index (HAQ-DI) score at the start of bDMARD treatment was associated with RPD. The cutoff value that discriminated progression from non-progression, determined by a receiver operating characteristic (ROC) curve, was 1.4375 (sensitivity: 0.778, specificity: 0.894). CONCLUSIONS: HAQ-DI score at the start of bDMARD treatment was associated with RPD to large joints during a therapeutic period of 1-3 years. Progressive damage is expected to increase when functional disability exceeds an HAQ-DI score of 1.5.

Predictors of severe radiographic progression in patients with early rheumatoid arthritis: A Prospective observational cohort study.

AIM: To identify predictors of severe radiographic progression in patients with early rheumatoid arthritis (ERA). METHODS: A total of 374 patients with ERA were selected from a Korean prospective cohort. Based on their annual Sharp/Van der Heijde modified score changes (ΔSHS/year), patients were classified into severe and no progression groups. Predictors of severe progression were evaluated using a multivariable logistic regression. RESULTS: After a mean follow-up duration of 4.2 years, the median (interquartile range) ΔSHS/year were 6.3 (4.4-10.2) and 0 (0-0) in the severe and no progression groups, respectively. Multivariable regression model revealed that Health Assessment Questionnaire (HAQ) score (odds ratio [OR] = 2.17), anticyclic citrullinated peptide antibody (OR = 3.44), body mass index (BMI; OR = 0.88), 6-month cumulative erythrocyte sedimentation rate (OR = 1.01) and baseline SHS (OR = 1.07) were independent predictors of severe progression. A model incorporating all five predictors satisfactorily predicted severe progression, with an area under the curve of 0.80. Baseline SHS was the predictor with the highest contribution to the predictive power of the final model (38%). CONCLUSIONS: Our predictive model composed of five clinical predictors showed high discriminative ability between severe and no radiographic progression in patients with ERA. Among them, baseline SHS was the strongest predictor. Also, low BMI in Korean patients with ERA have a high risk of severe radiographic progression, as has previously been found for Caucasians.