LOTIS‐5, AN ONGOING PHASE 3 RANDOMIZED STUDY OF LONCASTUXIMAB TESIRINE WITH RITUXIMAB (LONCA‐R) VERSUS IMMUNOCHEMOTHERAPY IN PATIENTS WITH <i>R</i>/<i>R</i> DLBCL
Bibliographic record
Abstract
+ DLBCL (de novo or transformed from follicular lymphoma [FL]): 1) DLBCL, not otherwise specified (NOS); 2) high-grade B-cell lymphoma with MYC and BCL-2 and/or BCL-6 rearrangement; 3) T-cell/histiocyte-rich LBCL; 4) Epstein-Barr virus-positive DLBCL, NOS; or 5) FL grade 3b.Other key eligibility criteria include IPI ≥2 (pts with IPI 2 not to exceed ~30% of total pts), ECOG PS 0-2, and ≥1 measurable disease site.Approximately 900 pts will be randomized 2:1 to either epcoritamab + R-CHOP (6 cycles, followed by 2 cycles of epcoritamab) or R-CHOP (6 cycles, followed by 2 cycles of rituximab).The primary efficacy endpoint is PFS in pts with IPI 3-5 (based on IRC assessment per Lugano criteria).The secondary efficacy endpoints are PFS in pts with IPI 2-5, eventfree survival, CMR, overall survival, and minimal residual disease negativity.Safety endpoints include incidence and severity of treatment-emergent adverse events (AEs), serious AEs, and AEs of special interest (CRS, immune cell-associated neurotoxicity syndrome, and clinical tumor lysis syndrome).Enrollment began in January 2023 globally.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".