Monoclonal Antibodies, Systemic Lupus Erythematosus, and Pregnancy: Insights from an Open-label Study
Bibliographic record
Abstract
To the Editor: Controlled clinical trials have revealed modest efficacy for the use of belimumab in the treatment of systemic lupus erythematosus (SLE)1,2. Followup of these patients has been published and of the 1458 patients who have received belimumab during phase II and III clinical trials, the most frequent events leading to discontinuation were lupus nephritis and infusion-related reactions3. We report herein the status of 47 patients who received open-label belimumab from a single-site cohort of patients whose longterm followup (mean 62 mos) could be ascertained. Pregnancy was found to be an atypical and potentially important reason for drug discontinuation that bears additional scrutiny. Study design and patient demographics for the first 52 and 76 weeks have been reviewed and published elsewhere1,2. Our initial cohort was composed of 55 patients in 2 double-blind, placebo-controlled trials: HGS-1056 and LBSL-02 (Figure 1). Twelve patients withdrew while blinded: 4 were receiving placebo and 8 withdrew because of pregnancy, flares (lupus nephritis, neuropsychiatric lupus), noncompliance, inefficacy, breast cancer, and the … Address correspondence to Dr. M.H. Weisman, 8700 Beverly Blvd., B131, Los Angeles, California 90048, USA. E-mail: weisman{at}cshs.org
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 | 0.021 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".