FACTORS ASSOCIATED WITH EFFICACY OF BELIMUMAB IN DIFFERENT JOINT AND SKIN PHENOTYPES OF SYSTEMIC LUPUS ERYTHEMATOSUS: PRELIMINARY DATA FROM THE MULTICENTER BERLISS-NEJS STUDY
Bibliographic record
Abstract
PV278 / #445 Poster Topic: AS24 - SLE-Treatment Background/Purpose To evaluate factors associated with belimumab’s efficacy on different skin and joint manifestations in a nationwide multicenter cohort (BeRLISS-NeJS) of patients with systemic lupus erythematosus (SLE). Methods In this retrospective observational study, adult SLE patients treated with belimumab (10 mg/kg/month IV or 200 mg/week SC) were stratified by joint (non-deforming nonerosive arthritis (NDNE), Jaccoud’s arthropathy, rhupus) and skin phenotypes (acute-ACLE, subacute-SCLE, chronic cutaneous lupus erythematosus-CCLE). We analyzed DAS28, CLASI-A, CLASI-D scores as well as DAS28 and CLASI-A remission rates (respectively DAS28<2.6 and CLASI-A=0) at 6, 12, 24, 36 months from baseline. Parametric and non-parametric tests were used according to data distribution. Results A total of 443 patients (88.9% female, mean treatment duration 30 months (range 12-60) were enrolled. At belimumab initiation, 272 patients (61.4%) had joint manifestations: 221 NDNE (50.7%), 30 Jaccoud’s arthropathy (6.9%), and 21 rhupus (4.8%); 231 patients (52.1%) had skin manifestations: 112 ACLE (25.3%), 54 SCLE (12.2%), 18 CCLE (4.1%), and 47 aspecific skin manifestations (10.6%). Patients with Jaccoud’s arthropathy or rhupus had a longer disease duration before belimumab initiation compared to NDNE patients. The NDNE subtype was associated with higher DAS28 remission rates than Jaccoud’s and rhupus at 6 and 36 months (Figure). Higher baseline DAS28 in NDNE patients correlated with lower remission rates at 6 and 12 months (p<0.001 and p=0.003). Smoking was associated with less probability to achieve remission at 12 months (p=0.003), while higher baseline prednisone intake was associated with higher remission rates at 12 months (p=0.046). Prior methotrexate treatment was negatively associated with remission at 6 and 24 months (p=0.006 and p=0.027), but concurrent methotrexate treatment did not affect remission rates. In Jaccoud’s patients, baseline DAS28 was not associated with remission rates. Prior methotrexate use was associated with lower remission rates at 12 months (p=0.027) and 36 months (p=0.022). In rhupus patients, higher baseline DAS28 was associated with lower remission rates at 6 months (p=0.016). Concurrent and prior methotrexate use did not influence remission rates. When considering remission in patients with skin manifestations, ACLE showed higher CLASI-A remission rate compared to the SCLE and CCLE at 18, 24, and 36 months (Figure). In ACLE patients, older age at belimumab initiation negatively correlated with CLASI remission at 6 (p=0.047) and 12 months (p=0.015). High baseline CLASI-A negatively impacted on remission at 6 (p<0.001), 12 (p=0.003), and 24 months (p=0.002), but not at 36 months (p=0.082). High baseline CLASI-D was associated with lower remission at 6 (p=0.002), 12 (p=0.030), and 24 months (p<0.001). In SCLE patients, high baseline CLASI-A was negatively associated with remission at 6 (p<0.001), 12 (p=0.001), and 24 months (p<0.001). High baseline CLASI-D correlated with lower remission rates at 6 (p=0.049), 12 (p=0.005), and 24 months (p=0.026). Anti-SSB antibodies at baseline negatively impacted on remission at 6 (p=0.025) and 24 months (p=0.012). In CCLE patients, high baseline CLASI-A negatively impacted remission at 24 months (p=0.016). Baseline CLASI-D did not affect remission; however, this subset had few patients. Figure. DAS28 and CLASI-A remission stratified for different joint and skin phenotypes, respectively. P values were assessed by Chi-squared test with Bonferroni corrextion (α=0.05). Please note that the p-values shown refer to the comparison in remission rotes among different phenotypes for that given timepoint. Conclusions Patients with NDNE arthritis and ACLE more frequently achieved DAS28 and CLASI-A remission, respectively. Univariate analyses indicated that active disease (high DAS28 and CLASI-A) and damage (high CLASI-D) at baseline were associated with lower remission rates, particularly in NDNE and ACLE patients. Prior methotrexate use was associated to lower remission rates, suggesting that methotrexate-refractory patients may benefit less from belimumab.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".