Organ damage in patients treated with belimumab versus standard of care: a propensity score-matched comparative analysis
Bibliographic record
Abstract
OBJECTIVES: The study (206347) compared organ damage progression in patients with systemic lupus erythematosus (SLE) who received belimumab in the BLISS long-term extension (LTE) study with propensity score (PS)-matched patients treated with standard of care (SoC) from the Toronto Lupus Cohort (TLC). METHODS: A systematic literature review identified 17 known predictors of organ damage to calculate a PS for each patient. Patients from the BLISS LTE and the TLC were PS matched posthoc 1:1 based on their PS (±calliper). The primary endpoint was difference in change in Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI) score from baseline to 5 years. RESULTS: For the 5- year analysis, of 567 (BLISS LTE n=195; TLC n=372) patients, 99 from each cohort were 1:1 PS matched. Change in SDI score at Year 5 was significantly lower for patients treated with belimumab compared with SoC (-0.434; 95% CI -0.667 to -0.201; p<0.001). For the time to organ damage progression analysis (≥1 year follow-up), the sample included 965 (BLISS LTE n=259; TLC n=706) patients, of whom 179 from each cohort were PS-matched. Patients receiving belimumab were 61% less likely to progress to a higher SDI score over any given year compared with patients treated with SoC (HR 0.391; 95% CI 0.253 to 0.605; p<0.001). Among the SDI score increases, the proportion of increases ≥2 was greater in the SoC group compared with the belimumab group. CONCLUSIONS: PS-matched patients receiving belimumab had significantly less organ damage progression compared with patients receiving SoC.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".