Rituximab Maintenance Therapy for Granulomatosis with Polyangiitis and Microscopic Polyangiitis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy compared to the relapse risk and tolerance of systematic rituximab (RTX) infusions as maintenance therapy for patients with granulomatosis with polyangiitis (GPA) or microscopic polyangiitis (MPA), who entered remission taking conventional immunosuppressants or RTX. METHODS: A retrospective study of the main clinical characteristics, outcomes, and RTX tolerance of patients who had received ≥ 2 RTX maintenance infusions in our center, regardless of induction regimen, between 2003 and 2010. RESULTS: We identified 28 patients [4 MPA and 24 GPA; median age 55.5 yrs (range 18-78); 17 (60%) males] who received a median of 4 (range 2-10) RTX maintenance infusions, with median followup of 38 months (range 21-97) since diagnosis or last flare. None experienced a RTX infusion-related adverse event; 15 patients (among the 21 with available data) had hypogammaglobulinemia (predominantly IgM) prior to their last RTX maintenance infusion; 3 had infectious events (1 cutaneous abscess, 1 otitis, 1 fatal H1N1 flu). Two patients suffered pulmonary relapses shortly before a planned RTX maintenance infusion (both had increased antineutrophil cytoplasmic antibody levels and 1 had CD19+ lymphocyte reconstitution). CONCLUSION: Rituximab maintenance therapy was well tolerated but did not completely prevent relapses and persistent "grumbling" disease. These preliminary results remain to be confirmed by a randomized controlled trial currently in progress.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".