Maintenance Therapy for CD20+ Indolent Lymphoma: Who Should Receive Maintenance?
Bibliographic record
Abstract
Maintenance rituximab (MR) has been a mainstay of treatment in Canada for CD20‑positive indolent lymphoma for two decades. The adoption of MR into clinical practice occurred after the publication of the EORTC 20981 trial. This trial showed a significant improvement in progression free survival (PFS) with two years of MR versus observation after induction therapy with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) or rituximab with cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) in patients with relapsed follicular lymphoma (FL). The use of MR was broadly extended to include its use in the front‑line setting, following any R-containing inductions and including all CD20-positive indolent lymphoma histologies. Automatic recommendations for MR became the standard practice for most patients. Given the recent changes to standard induction regimens in some indications, and with heightened concerns about infectious complications during B-cell depleting therapy, the recommendation for the use of MR should no longer be considered automatic. This review offers a balanced perspective of the evidence for MR.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".