Three Clinical Clusters Identified through Hierarchical Cluster Analysis Using Initial Laboratory Findings in Korean Patients with Systemic Lupus Erythematosus

Patients' Preferences for Systemic Lupus Erythematosus Treatments-A Discrete Choice Experiment

BACKGROUND

Symptoms of systemic lupus erythematosus (SLE) vary between patients, but those of increased disease activity typically include musculoskeletal and mucocutaneous manifestations such as joint pain, swelling, and rashes. Several treatment options are available to patients with SLE with variable efficacy. Many treatments, especially corticosteroids, cause unwanted side effects, although little is currently known about patients' preferences for treatments of SLE.

OBJECTIVE

We aimed to identify which attributes of SLE treatment are valued by patients and to quantify their relative importance.

METHODS

Adult participants with moderate-to-severe SLE were asked to make a series of choices between two hypothetical treatments in an online discrete choice experiment (DCE). A latent class model (LCL) was estimated to analyze choice data. Relative attribute importance (RAI) was calculated to determine the importance of each attribute to participants.

RESULTS

A total of 342 participants from the USA completed the survey. A three-class LCL model was found to have the best fit. Class 1 (non-attenders) had non-significant preferences across all attributes. To achieve a better fit, a constrained LCL (cLCL) model was run with the two remaining classes. The most important attributes for participants in class 2 (benefit-seekers) were joint pain (RAI = 32.0%), non-joint pain (RAI = 21.8%), fatigue (RAI = 20.1%), and skin rashes and itching (RAI = 19.1%). The most important attributes for participants in class 3 (risk-avoiders) were risk of non-severe side effects from corticosteroids (RAI = 28.4%), risk of severe side effects from corticosteroids (RAI = 21.4%), and the risk of infections (RAI = 19.2%). Risk-avoiders were more likely to have been diagnosed with SLE for a longer period (>1 year) and were more likely to have experience with oral corticosteroids.

CONCLUSIONS

SLE patients fall into two groups with distinct preferences: benefit-seekers, who prioritize reducing the impact of disease symptoms, and risk-avoiders, who prioritize avoiding treatment risks. The implication of this finding will depend on the reasons for these differences, which warrant further research. Our study suggests that these differences arise due to the impact of disease and treatment experience on preferences. If so, well-informed patients may not be willing to tolerate the risks associated with oral corticosteroids in exchange for their benefits.

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

OBJECTIVES

A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes.

METHODS

Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset.

RESULTS

Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2.

CONCLUSION

Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.

Complement as a Biomarker for Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a disease of immune complex deposition; therefore, complement plays a vital role in the pathogenesis of SLE. In general, complement levels in blood and complement deposition in histological tests are used for the management of SLE. Thus, the evaluation of complement status can be useful in the diagnosis of SLE, assessment of disease activity, and prediction of treatment response and prognosis. In addition, novel complement biomarkers, such as split products and cell-bound complement activation products, are considered to be more sensitive than traditional complement markers, such as serum C3 and C4 levels and total complement activity (CH50), which become more widely used. In this review, we report the complement testing in the management of SLE over the last decade and summarize their utility.

Clinical Heterogeneity, Unmet Needs and Long-Term Outcomes in Patients with Systemic Lupus Erythematosus

The clinical presentation of systemic lupus erythematosus (SLE) is highly heterogeneous, ranging from mild disease limited to skin and joint involvement to life-threatening conditions with renal impairment, severe cytopenias, central nervous system disease, and thromboembolic events [...].