Rituximab Extended Schedule or Re-Treatment Trial for Low–Tumor Burden Follicular Lymphoma: Eastern Cooperative Oncology Group Protocol E4402
Bibliographic record
Abstract
PURPOSE: In low-tumor burden follicular lymphoma (FL), maintenance rituximab (MR) has been shown to improve progression-free survival when compared with observation. It is not known whether MR provides superior long-term disease control compared with re-treatment rituximab (RR) administered on an as-needed basis. E4402 (RESORT) was a randomized clinical trial designed to compare MR against RR. PATIENTS AND METHODS: Eligible patients with previously untreated low-tumor burden FL received four doses of rituximab, and responding patients were randomly assigned to either RR or MR. Patients receiving RR were eligible for re-treatment at each disease progression until treatment failure. Patients assigned to MR received a single dose of rituximab every 3 months until treatment failure. The primary end point was time to treatment failure. Secondary end points included time to first cytotoxic therapy, toxicity, and health-related quality of life (HRQOL). RESULTS: A total of 289 patients were randomly assigned to RR or MR. With a median follow-up of 4.5 years, the estimated median time to treatment failure was 3.9 years for patients receiving RR and 4.3 years for those receiving MR (P = .54). Three-year freedom from cytotoxic therapy was 84% for those receiving RR and 95% for those receiving MR (P = .03). The median number of rituximab doses was four patients receiving RR and 18 for those receiving MR. There was no difference in HRQOL. Grade 3 to 4 toxicities were infrequent in both arms. CONCLUSION: In low-tumor burden FL, a re-treatment strategy uses less rituximab while providing disease control comparable to that achieved with a maintenance strategy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".