Detecting the earliest signs of rheumatoid arthritis: symptoms and examination

The Symptoms in Persons At Risk of Rheumatoid Arthritis (SPARRA) questionnaire: predicting clinical arthritis development

OBJECTIVE

There is a need to better define symptom characteristics associated with arthritis development in individuals at risk of rheumatoid arthritis (RA). We investigated whether reported symptoms in at-risk individuals could predict arthritis development and whether predictive symptoms differed between seropositive and seronegative at-risk individuals.

METHOD

At-risk individuals from four cohorts (Netherlands, UK, Sweden, and Switzerland) completed the Symptoms in Persons At Risk of Rheumatoid Arthritis (SPARRA) questionnaire. Participants had either (i) anti-citrullinated protein antibodies and/or rheumatoid factor, or (ii) relevant symptoms with or without RA antibodies. Follow up was ≥ 24 months or until clinical arthritis development. Stepwise forward selection created SPARRA prediction models for the combined group and for a seropositive subgroup.

RESULTS

Of 214 participants, the mean age was 50 years, 67% were female, and 27% (n = 58) developed clinical arthritis after a median time of 7 months. Four symptoms predicted arthritis development: self-reported joint swelling, joint pain moving from side to side (combined group only), feeling pins and needles in the joints, and often feeling fatigued (predicting non-arthritis).

CONCLUSION

Specific symptoms can provide useful information to estimate a person's RA risk. Differences in predictive symptoms between seropositive and seronegative at-risk individuals need to be further investigated. Future research is needed to determine whether changes in symptoms over time improve prediction and to determine the value of SPARRA in optimizing the selection of individuals who need to consult a rheumatologist.

A pilot study of a machine-learning tool to assist in the diagnosis of hand arthritis

OBJECTIVE

Arthritis is a common condition, which frequently involves the hands. Patients with inflammatory arthritis have been shown to experience significant delays in diagnosis. We sought to develop and test a screening tool combining an image of a patient's hands, a short series of questions, and a single examination technique, to determine the most likely diagnosis in a patient presenting with hand arthritis. Machine learning techniques were used to develop separate algorithms for each component, which were combined to produce a diagnosis.

METHODS

280 consecutive new patients presenting to a Rheumatology practice with hand arthritis were enrolled. Each patient completed a 9-part questionnaire, had photographs taken of each hand, and had a single examination result recorded. The Rheumatologist diagnosis was recorded following a 45-minute consultation. The photograph algorithm was developed from 1000 previous hand images, and machine learning techniques were applied to the questionnaire results, training several models against the diagnosis from the Rheumatologist.

RESULTS

The combined algorithms in this study were able to predict inflammatory arthritis with an accuracy, precision, recall and specificity of 96·8%, 97·2%, 98·6% and 90·5% respectively. Similar results were found when inflammatory arthritis was subclassified into rheumatoid arthritis and psoriatic arthritis. The corresponding figures for osteoarthritis were 79·6%, 85·9%, 61·9% and 92·6%.

CONCLUSION

This study demonstrates a novel application combining image-processing and a patient questionnaire with applied machine-learning methods, to facilitate the diagnosis of patients presenting with hand arthritis. Preliminary results are encouraging for the application of such techniques in clinical practice. This article is protected by copyright. All rights reserved.

Radiographic changes in TMJ in relation to serology and disease activity in RA patients

OBJECTIVES

This study was undertaken as an attempt to assess radiographic temporomandibular joint (TMJ) changes in relation to rheumatoid factor (RF), anticitrullinated protein (ACCP) antibodies and disease activity score 28 (DAS28) in rheumatoid arthritis (RA) patients to find the best predictor of rheumatoid affection of the TMJ with the ultimate goal of maintaining TMJ function and preventing joint damage.

METHODS

20 Rheumatoid Arthritis patients as well as 20 volunteers were included in this study. RA group were assessed for RF, ACCP, DAS28. Both groups were assessed by CBCT for TMJ dimensions and radiographic osteoarthritic changes. All data were statistically analyzed.

RESULTS

Rheumatoid Arthritis group showed significantly less condylar height and more radiographic osteoarthritic changes than the control group. RF showed no significant correlation with either TMJ measurements or TMJ radiographic osteoarthritic changes. ACCP showed significant inverse correlation with condylar height and anteroposterior (AP) dimensions, but non-significant relation with mediolateral dimension and radiographic osteoarthritic changes. DAS28 showed significant inverse correlation with condylar AP and mediolateral dimensions. It also showed significant correlation with flattening of the TMJ condylar head and flattening of the articular fossa. Patients with high and moderate disease activity showed significantly smaller AP TMJ dimension than patients with low disease activity. Disease activity showed statistically significant direct correlation with all osteoarthritic changes except for erosions of the glenoid fossa and condyle.

CONCLUSION

Disease Activity Score28 score and disease activity are strong indicators of TMJ affection in RA patients when compared to RF and ACCP. ACCP is a better indicator of changes in condylar measurements than TMJ osteoarthritic changes. While RF is the least efficient indicator of TMJ involvement in RA patients.

Initial validation and results of the Symptoms in Persons At Risk of Rheumatoid Arthritis (SPARRA) questionnaire: a EULAR project

Objectives

To describe the development and assess the psychometric properties of the novel 'Symptoms in Persons At Risk of Rheumatoid Arthritis' (SPARRA) questionnaire in individuals at risk of rheumatoid arthritis (RA) and to quantify their symptoms.

Methods

The questionnaire items were derived from a qualitative study in patients with seropositive arthralgia. The questionnaire was administered to 219 individuals at risk of RA on the basis of symptoms or autoantibody positivity: 74% rheumatoid factor and/or anticitrullinated protein antibodies positive, 26% seronegative. Validity, reliability and responsiveness were assessed. Eighteen first degree relatives (FDR) of patients with RA were used for comparison.

Results

Face and content validity were high. The test-retest showed good agreement and reliability (1 week and 6 months). Overall, construct validity was low to moderate, with higher values for concurrent validity, suggesting that some questions reflect symptom content not captured with regular Visual Analogue Scale pain/well-being. Responsiveness was low (small subgroup). Finally, the burden of symptoms in both seronegative and seropositive at risk individuals was high, with pain, stiffness and fatigue being the most common ones with a major impact on daily functioning. The FDR cohort (mostly healthy individuals) showed a lower burden of symptoms; however, the distribution of symptoms was similar.

Conclusions

The SPARRA questionnaire has good psychometric properties and can add information to currently available clinical measures in individuals at risk of RA. The studied group had a high burden and impact of symptoms. Future studies should evaluate whether SPARRA data can improve the prediction of RA in at risk individuals.

Detecting changes in arthritic fibroblast-like synoviocytes using atomic force microscopy

The morphological and quantitative differences between arthritic fibroblast-like synoviocytes (FLS) and normal FLS were determined as an effective diagnostic tool for rheumatoid arthritis (RA), and confirmed using atomic force microscopy (AFM). Collagen-induced arthritic (CIA) mice and normal mice were prepared and FLS were isolated by enzymatic digestion from the synovial tissue of sacrificed mice at 5-week and 8-week pathogenesis periods. Analysis of cell morphology using AFM revealed that the surface roughness around the nucleus and around the branched cytoplasm was significantly higher in CIA FLS (P < 0.05) than that in normal FLS. In addition, the roughness of two different sites on the arthritic FLS increased with an increase in the duration of pathogenesis. These results strongly suggest that AFM can be widely used as a diagnostic tool in cytopathology to detect the early signs of RA and various others diseases at the intercellular level.