Cost–effectiveness of rituximab in follicular lymphoma
Bibliographic record
Abstract
In advanced follicular lymphoma, rituximab is currently used with chemotherapy as induction therapy, and as maintenance monotherapy following induction in previously untreated patients and treatment-experienced relapsed/refractory patients. Herein, the authors characterize the clinical effectiveness, safety and cost-effectiveness of rituximab in follicular lymphoma, based on the literature review. Rituximab has a favorable safety profile and has been shown to improve progression-free survival, with some evidence of improvements to overall survival, particularly for relapsed/refractory patients. Rituximab has consistently been found to have a favorable economic profile, with cost per quality-adjusted life year falling within standard thresholds for cost-effectiveness. Challenges in cost-effectiveness analysis include the fact that life expectancy for patients with follicular lymphoma exceeds the period of available follow-up data and that treatment pathways are more complex than the model structures frequently used in oncology models. As data accrue and more complex models are developed, the cost-effectiveness of rituximab can be more accurately assessed.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".