O15. Response to Rituximab in Patients with Refractory Systemic Lupus Erythematosus (SLE): Results from a National Multi-Centre Register
Bibliographic record
Abstract
Background: Published efficacy data for rituximab in SLE are complex with positive single-centre case series and negative randomized controlled trials. This may be due to heterogeneity of SLE or the populations, study design or endpoints of trials. The BILAG Biologic Registry (BILAG BR) is a national, multicentre, prospective study which aims to determine the safety and efficacy of biologics in SLE patients refractory to standard immunosuppressive therapy. The objective of the present analysis is to describe clinical response to rituximab at 3 and 6 months post therapy. Methods: Patients with SLE (≥4 ACR 1997 criteria), ≥5 years old, refractory to conventional therapy and newly starting treatment with rituximab, from centres across the UK, were recruited into the BILAG BR. A comprehensive questionnaire collected information on concomitant medications, risk factors for infection, co-morbidities and SLE disease duration. Disease activity was measured using the BILAG 2004 Index and the SLEDAI 2000 (SLEDAI-2K) at treatment initiation and at 3 and 6 months post therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".