[Clinical significance of determination of DFS70 antibodies to rule out connective tissue diseases]

Exploring the predictive power of antinuclear antibodies and Rheumatoid factor correlations in anticipating therapeutic outcomes for female patients with coexisting Sjögren's syndrome and Rheumatoid arthritis

Background

Sjögren's Syndrome (SS) and Rheumatoid Arthritis (RA) are autoimmune conditions that often coexist in female patients. Biomarkers such as antinuclear antibodies (ANA) and rheumatoid factor (RF) are used for diagnosis, but their predictive power for treatment outcomes remains unclear. This study aims to investigate the correlation between age, ANA, RF, and treatment response in female patients with both SS and RA.

Objective

To evaluate the relationships between age, ANA, RF levels, RA (disease present), and treatment response using Pearson correlation analysis and a neural network model, to predict treatment outcomes in patients with coexisting SS and RA.

Methods

A cohort of 56 female patients aged 30-73 was analyzed. Descriptive statistics provided an overview of key variables, followed by Pearson correlation analysis to assess relationships between age, ANA, RF, RA, and treatment response. A neural network model was developed to predict treatment response based on age, ANA, and RF levels, using a training-to-testing split of 81.3 % and 18.8 %, respectively.

Results

The Pearson correlation analysis revealed a significant positive correlation between age and ANA levels (r = .541, p = 0.031), though no significant correlations were found between age, RF, RA, and treatment response. The neural network model achieved an accuracy of 92.3 % during training and 100 % accuracy during testing for most treatment categories. However, the model struggled to accurately distinguish between certain classes, particularly treatment categories 1 and 3.

Conclusion

Age showed a significant correlation with ANA levels, indicating that older patients may have elevated ANA. The neural network model demonstrated strong predictive power for treatment response, although further refinement is needed to improve its ability to distinguish between all response categories. These findings suggest that machine learning models could enhance personalized treatment strategies for patients with SS and RA, but additional validation with larger datasets is required.

The significance of dense fine speckled pattern in antinuclear antibody-associated rheumatic disease and coexisting autoantibodies: A propensity score-matched cohort study

AIM

To investigate the relationship between the prevalence of antinuclear antibody (ANA) -associated rheumatic diseases (AARD) and the presence of dense fine speckled (DFS) and homogeneous patterns in ANA tests.

METHODS

This retrospective study enrolled adult patients with either a DFS or homogeneous pattern in their ANA test. A mixed pattern was defined as the presence of more than one pattern reported in the test. The presence of anti-DFS70 antibodies and other common autoantibodies were detected using EUROLINE ANA Profile 23. A 1:2 propensity score matching was applied to control for demographic and other interfering factors.

RESULTS

A total of 59 patients with a DFS pattern were enrolled and compared with a matched homogeneous group. The DFS group had a significantly lower prevalence of AARD (3.4% vs. 16.9%, p = .008) and the subgroup with anti-DFS70 antibodies showed an even lower prevalence (2% vs. 20%, p = .002). Among the 33 patients with monospecific anti-DFS70 antibodies, five had a mixed pattern, and all patients with common autoantibodies had an isolated DFS pattern.

CONCLUSIONS

The findings of this study suggest that patients with a DFS pattern in their ANA test may have a lower prevalence of AARD compared with those with a homogeneous pattern. However, an isolated DFS pattern in ANA testing does not necessarily indicate the presence of monospecific anti-DFS70 antibodies or AARD. Confirmatory testing for the monospecific anti-DFS70 antibody is mandatory to exclude AARD.

Autoantibodies to dense-fine-speckled 70 (DFS70) do not necessarily rule out connective tissue diseases

OBJECTIVES

In some patients with antinuclear antibodies (ANA), a pattern called anti-dense-fine-speckled-70 antibody (anti-DFS70) can be detected. Presence of anti-DFS70 is less frequently observed in patients with connective tissue diseases (CTD) and is therefore used as an exclusion criterion by some rheumatologists. To date, however, it is unclear as to what extent the presence of an anti-DFS70 can reliably rule out CTDs.

METHODS

Data of 460 patients who were tested for the presence of anti-DFS70 at University Hospital Bonn, Germany, were analyzed. Patients were examined with regard to clinical symptoms and signs, type of disease, type of CTD, fulfillment of the classification criteria, presence of anti-DFS70, other systemic autoantibodies and ANA titers by indirect immunofluorescence (IIF) assays and line immunoassays. Differences in DFS70 antibody status between patients with CTD were examined. In addition, specificity, sensitivity, and positive predictive values for different ANA titers were calculated.

RESULTS

In 182 of the 460 patients (of whom 79.8% were female), CTD was diagnosed. 354 patients (77.0%) tested negative, 81 (17.6%) positive and 25 (5.4%) borderline for anti-DFS70. Twenty-one patients (25.9%) with a positive result had CTD. No significant differences were observed between anti-DFS70 positive and anti-DFS70 negative patients with CTD concerning age, gender, symptoms, clinical signs, and other disease-specific antibodies. However, of these 21 patients, only one patient showed the monospecific appearance of anti-DFS70. Anti-DFS70 had a sensitivity and a specificity of 26.9% and 86.8%, respectively, with a positive predictive value of 68.2% at an ANA titer of ≥1:160 with respect to the absence of CTD.

CONCLUSIONS

Autoantibodies to DFS70 seem to be prevalent in CTD patients and are thus not a good exclusion criterion. The monospecific occurrence of anti-DFS70 can, however, be helpful in ambiguous situations.

Anti-DFS70 Antibodies for Differentiating Systemic Autoimmune Rheumatic Disease in Patients with Positive ANA Tests: A Systematic Review and Meta-Analysis

Anti-DFS70 antibodies have been proposed as a marker to exclude systemic autoimmune rheumatic disease (SARD). We conducted this systematic diagnostic test accuracy review and meta-analysis to determine the performance of anti-DFS70 antibodies in patients with a positive anti-nuclear antibody (ANA) test result to exclude SARD. We searched PubMed, Embase, Web of Science, Scopus and the Cochrane Library up to 22 February 2021, and included studies examining the diagnostic accuracy of anti-DFS70 antibodies in patients with a positive ANA test result. The results were pooled using a hierarchical bivariate model and plotted in summary receiver operating characteristic curves. R software and Stata Statistical Software were used for the statistical analysis. Eight studies with 4168 patients were included. The summary sensitivity was 0.19 (95% confidence interval: 0.12–0.28) and the specificity was 0.93 (95% confidence interval: 0.88–0.96). The area under the curve was 0.69 (95% confidence interval: 0.64–0.72). The meta-regression analysis showed that targeting only ANA-associated rheumatic disease was associated with higher specificity. In addition, the studies with a non-SARD prevalence of <80% and using a chemiluminescence assay were associated with higher specificity. Anti-DFS70 antibodies have high specificity for the exclusion of SARD among patients presenting with a positive ANA test, but the sensitivity is low.