A Global Survey of Quinacrine Use in Systemic and Cutaneous Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Experiences with the antimalarial quinacrine for systemic lupus erythematosus (SLE) and cutaneous lupus erythematosus (CLE) remain underexplored. We evaluated and compared dermatologists' and rheumatologists' experiences with quinacrine in managing SLE and/or CLE. METHODS: We sent a structured survey to 102 SLE specialists within the Systemic Lupus International Collaborating Clinics (SLICC) and the Canadian Network for Improved Outcomes in Systemic Lupus Erythematosus (CaNIOS), and 200 members of the Rheumatologic Dermatology Society (RDS). Participants responded to questions on self-reported quinacrine prescription history, perceived clinical benefit, reasons for drug discontinuation, and barriers to prescribing. RESULTS: A total of 20 dermatologists from RDS and 40 SLICC and CaNIOS members responded to the survey. All RDS participants (100%) had previously prescribed quinacrine, compared to 17/40 (43%) of SLICC/CaNIOS participants. The majority of quinacrine prescribers (100% RDS, 12/17 [71%] SLICC/CaNIOS) had prescribed quinacrine in combination with another antimalarial. Hydroxychloroquine (HCQ) or chloroquine (CQ) intolerance (65% RDS, 47% SLICC/CaNIOS) and HCQ/CQ-related retinal toxicity (50% RDS, 24% SLICC/CaNIOS) were other reasons for prescribing quinacrine. Clinical benefit was reported by 19/20 (95%) of RDS and 12/17 (71%) of SLICC/CaNIOS clinicians, and discontinuations were less frequent among RDS (5/20 [25%] reported none) compared to SLICC/CaNIOS (all 17 reported ≥ 1). Availability and cost of quinacrine were primary prescribing barriers. CONCLUSION: Surveyed dermatologists and rheumatologists differed in their experience with quinacrine for CLE and SLE, respectively. Availability remains a key barrier to prescribing, underscoring the need to address supply issues and conduct further research to optimize quinacrine use in SLE and CLE.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".