Rituximab in primary central nervous system lymphoma—A systematic review and meta‐analysis
Bibliographic record
Abstract
The CD-20 antibody rituximab is a standard component of treatment of non-Hodgkin B-cell lymphomas, including diffuse large B-cell lymphoma (DLBCL). Primary DLBCL of the central nervous system, also called primary central nervous system lymphoma (PCNSL), is a DLBCL confined to the central nervous system. There has been debate whether intravenous rituximab accumulates sufficiently in the central nervous system to exert an effect. In this systematic review, we assess the benefits and harms of rituximab in the treatment of immunocompetent patients with PCNSL. By searching MEDLINE, CENTRAL, and ClincialTrials.gov up to March 2019, we identified randomized controlled trials (RCTs) investigating the effect of rituximab in patients with PCNSL. We extracted study characteristics and results, assessed risk of bias, performed trial-level random-effects meta-analyses, and graded the certainty of evidence. The protocol was registered with PROSPERO (CRD42019121965). Main outcomes were overall survival (time to death), progression-free survival (time to progression or death), quality of life, grades 3 and 4 toxicity, and treatment-related mortality. We included two RCTs with a total of 343 participants. Overall survival was not statistically significantly improved (HR 0.76; 95% CI, 0.52-1.12; low certainty), with 187 fewer to 39 more deaths after 2 years in 1000 treated patients. Low certainty of evidence indicated that rituximab improved progression-free survival (HR 0.65; 95% CI, 0.45-0.95), which translated into 137 fewer progressions or deaths after 2 years in 1000 treated patients (231 to 18 fewer). None of the RCTs provided data on quality of life. We found no evidence that rituximab increased grades 3 and 4 toxicity or treatment-related mortality (RR 0.53; 95% CI, 0.20-1.37; low certainty). Overall, the available evidence suggests with low certainty that rituximab in combination with methotrexate-based chemotherapy may improve progression-free survival in immunocompetent patients with newly diagnosed PCNSL, the pooled effect estimates did not show evidence for improvement of overall survival.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".