Glofitamab in Relapsed/Refractory Mantle Cell Lymphoma: Results From a Phase I/II Study
Bibliographic record
Abstract
PURPOSE: Patients with relapsed/refractory (R/R) mantle cell lymphoma (MCL) have a poor prognosis. The phase I/II NP30179 study (ClinicalTrials.gov identifier: NCT03075696) evaluated glofitamab monotherapy in patients with R/R B-cell lymphomas, with obinutuzumab pretreatment (Gpt) to mitigate the risk of cytokine release syndrome (CRS) with glofitamab. We present data for patients with R/R MCL. METHODS: Eligible patients with R/R MCL (at least one previous therapy) received Gpt (1,000 or 2,000 mg) 7 days before the first glofitamab dose (single dose or split over 2 days if required). Glofitamab step-up dosing was administered once a day on days 8 (2.5 mg) and 15 (10 mg) of cycle 1, with a target dose of 16 or 30 mg once every 3 weeks from cycle 2 day 1 onward, for 12 cycles. Efficacy end points included investigator-assessed complete response (CR) rate, overall response rate (ORR), and duration of CR. RESULTS: Of 61 enrolled patients, 60 were evaluable for safety and efficacy. Patients had received a median of two previous therapies (range, 1-5). CR rate and ORR were 78.3% (95% CI, 65.8 to 87.9) and 85.0% (95% CI, 73.4 to 92.9), respectively. In patients who had received previous treatment with a Bruton tyrosine kinase inhibitor (n = 31), CR rate was 71.0% (95% CI, 52.0 to 85.8) and ORR was 74.2% (95% CI, 55.4 to 88.1). CRS after glofitamab administration occurred in 70.0% of patients, with a lower incidence in the 2,000 mg (63.6% [grade ≥2, 22.7%]) versus 1,000 mg (87.5%; grade ≥2, 62.5%) Gpt cohort. Four adverse events led to glofitamab withdrawal (all infections). CONCLUSION: Fixed-duration glofitamab induced high CR rates in heavily pretreated patients with R/R MCL; the safety profile was manageable with appropriate support.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".