Rituximab Cerebrospinal Fluid Levels in Patients with Primary Central Nervous System Lymphoma Treated with Intravenous High Dose Rituximab
Bibliographic record
Abstract
Abstract Abstract 1644 INTRODUCTION: Rituximab penetration in central nervous system is largely unknown in human. Experiments in monkeys showed that 0,1% of serum rituximab concentration was achieved in cerebrospinal fluid. Reports in patients are limited (Rubenstein JL, Blood 2003 and Petereit HF, Multiple Sclerosis 2009). They demonstrated similar low levels of cerebrospinal fluid penetration with standard dose (375 mg /m2) rituximab in patients with central nervous system (CNS) lymphoma or multiple sclerosis. METHOD: We conducted a phase 2 trial in patients with primary CNS lymphoma. Patients were treated with an intravenous combination of high dose methotrexate (8 g/m2), high dose cytarabine (2 g/m2) and high dose rituximab (750 mg/m2 every 1–2 weeks × 13 infusions). We obtained from four patients paired cerebrospinal fluid and serum samples and rituximab concentration were determined in each. Samples were collected at different time points just before rituximab infusion and represent trough levels. RESULTS: 11 cerebrospinal fluid samples were available and their 11 paired serum samples. Mean cerebrospinal fluid and serum levels were 2,04 ug/mL (0,49–4,08) and 297,09 ug/mL (211,26–504,47) respectively. Mean cerebrospinal fluid levels were 0,71% (0,18–1,5%) of serum levels. No relationship was made between cerebrospinal fluid level and the number of rituximab dose administered. CONCLUSION: In patients with primary CNS lymphoma receiving high dose 1–2 weekly rituximab. cerebrospinal fluid concentration achieve is low compared to serum levels. However, administration of higher dose of intravenous rituximab can increase penetration in central nervous system but its clinical impact is unknown as cerebrospinal fluid levels are still low. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".