Is antimalarial use associated with a reduced risk of LN in patients with SLE? Results from an inception cohort-based study
Bibliographic record
Abstract
OBJECTIVES: Antimalarials are a cornerstone in managing SLE and are associated with multiple favourable disease outcomes. This study explored whether antimalarial use is associated with a reduced risk of incident LN in SLE patients. METHODS: We included SLE patients from an inception cohort with no prior history of LN, followed prospectively at regular intervals. The relationship between the exposure (cumulative duration of antimalarial exposure in years) and the outcome (development of LN, as indicated by new-onset proteinuria attributed to lupus activity by clinical judgement and recorded in the SLEDAI-2K sheet) was characterized using a time-dependent univariable Cox proportional hazards model to estimate the overall effect. Adjusted multivariable Cox regression was also employed to estimate the risk of LN, incorporating clinically relevant variables. RESULTS: The study included 674 inception SLE patients, with a median baseline age of 33.6 years (interquartile range [IQR]: 24.9-45.4). One hundred and fifty-four patients (22.8%) developed SLE-related new-onset proteinuria, indicating LN, with a median time to event of 3.6 years [IQR: 0.9-8.8]. Cumulative duration of antimalarial exposure was not significantly associated with a lower risk of LN, either in the unadjusted univariable model estimating the overall effect (hazard ratio [HR]: 0.98; 95% CI: 0.94-1.02, P = 0.25) or in the adjusted multivariable model (HR: 0.96; 95% CI: 0.92-1.00, P = 0.08). This finding was also corroborated in a sensitivity analysis of patients with serologically active SLE (HR: 0.97; 95% CI: 0.92-1.02). CONCLUSION: Antimalarial use is not significantly associated with a reduced risk of incident LN in SLE 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".