COMPARATIVE EFFECTS OF BIOLOGICS AND SMALL MOLECULE INHIBITORS ON CUTANEOUS DISEASE ACTIVITY IN SYSTEMIC AND CUTANEOUS LUPUS ERYTHEMATOSUS: A SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS
Bibliographic record
Abstract
O055 / #488 Topic:AS07 - Cutaneous Lupus ABSTRACT CONCURRENT SESSION 09: SLE THERAPY – REVISITING OLD DRUGS AND UNLOCKING HIDDEN POTENTIAL OF NEW MEDICATIONS 24-05-2025 10:40 AM - 11:40 AM Background/Purpose Cutaneous lupus erythematosus (CLE) is a debilitating and disfiguring disease that can occur with systemic lupus erythematosus (SLE) or independently. CLE is burdensome and impairs quality of life. Despite treatment with glucocorticoids, antimalarials, and traditional immunosuppressive treatments, cutaneous disease in LE represents an ongoing therapeutic challenge; yet biological agents and small molecule inhibitors show promise. The exclusion of most CLE patients from LE trials designed for SLE has resulted in a lack of approved treatments for CLE. Furthermore, skin disease improvement in LE is often only recorded as a secondary outcome in these trials. We conducted a systematic review and network meta-analysis to summarize the existing biological agents and small molecule inhibitors used to treat LE and their comparative effect on CLE disease activity. Methods We systematically searched MEDLINE, Embase, and CENTRAL to October 6th, 2024, for randomized controlled trials (RCTs) assessing the impact of biologics and/or small molecule inhibitors on cutaneous disease activity, as measured by Cutaneous LE Disease Area and Severity Index-Activity scores (CLASI-A, 0-70, lower scores better) in patients with cutaneous or systemic LE. Pairs of reviewers independently screened citations. We extracted relevant trial characteristics and CLASI-A outcome data according to the intention-to-treat principle and assessed risk of bias using Cochrane’s Risk of Bias 2.0 tool for RCTs. Random effects network meta-analyses pooled effect estimates for the probability of achieving CLASI-50 (a 50% improvement in baseline CLASI-A scores). We applied the GRADE approach to inform our ratings of the certainty of evidence. Results We identified 43 unique RCTs randomizing 8,725 patients with systemic or cutaneous LE (median [range] of mean age: 42.8 [30.6-54.0] years; median 93% female). Most RCTs evaluated improvement in CLASI-A scores as a secondary outcome (n = 39, 91%). The median (range) CLASI-A score at baseline was 7.8 (2.53-23.5) points. A total of 33 unique interventions were evaluated across the included studies (Figure 1). Seven (16%) trials were judged to be at a high risk of bias, with common reasons being early termination of the trial and high rates of missing outcome data. Compared to placebo, high certainty evidence shows that anifrolumab increases the probability of achieving CLASI-50 (odds ratio [OR] 2.14, 95% CI 1.34-3.42; risk difference [RD] 18.8% more, 95% CI 7.3%-29.1%; Figure 2). Moderate certainty evidence suggests that deucravacitinib (OR 8.28, 95% CI 2.53-27.06; RD 43.2% more, 95% CI 22.6%-52.3%), litifilimab (OR 2.24, 95% CI 1.20-4.18; RD 19.8% more, 95% CI 4.5%-32.9%), and sifalimumab (OR 2.33, 95% CI 1.03-5.29; RD 20.7% more, 95% CI 0.7%-37.0%) increase the probability of achieving CLASI-50. Low certainty evidence suggests that daxdilimab (OR 3.11, 95% CI 0.72-13.43; RD 27.1% more, 95% CI 7.8% fewer to 48.0% more) may increase the probability of achieving CLASI-50. Baricitinib and iberdomide probably have little to no difference on CLASI-50 responses (moderate certainty) and brepocitinib may have little to no difference on CLASI-50 responses (low certainty). Figure 1. Figure 2. Conclusions Among patients with systemic or cutaneous LE, anifrolumab, deucravacitinib, litifilimab, and sifalimumab increased the probability of achieving CLASI-50 response compared to placebo. These agents act by inhibiting part of the type-1 interferon pathway and may have clinical utility in improving the lives of CLE patients.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.032 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".