Talquetamab plus daratumumab for the treatment of relapsed or refractory multiple myeloma in the TRIMM-2 study
Bibliographic record
Abstract
ABSTRACT: Talquetamab, a G protein-coupled receptor class C group 5 member D-targeting bispecific antibody for relapsed/refractory multiple myeloma (R/R MM), plus daratumumab, may lead to deeper and more durable responses than either therapy alone. In the phase 1b TRIMM-2 study, patients with R/R MM (at least 3 previous lines of therapy or double refractory to a proteasome inhibitor and an immunomodulatory drug) received subcutaneous talquetamab 0.4 mg/kg weekly (QW; "QW cohort") or 0.8 mg/kg every other week (Q2W cohort) plus daratumumab 1800 mg per the approved schedule. The primary end point was safety. Secondary end points included overall response and duration of response. Progression-free survival was an exploratory end point. Sixty-five patients (median 5 previous lines of therapy; 61.5% triple-class refractory; 24.6% bispecific antibody exposed) received talquetamab plus daratumumab (QW, n = 14; Q2W, n = 51; median follow-up of 18.6 months). Most common adverse events were oral events, skin events, cytokine release syndrome, and infections. Grade 3 or 4 events occurred in 81.5%. Two patients had dose-limiting toxicities, both in the Q2W cohort (grade 3 stomatitis/oral mucositis, and grade 3 maculopapular rash). Responses occurred in 71.4% (QW cohort) and 82.4% (Q2W cohort) of patients. Median progression-free survival was 23.3 and 21.2 months, respectively, in each cohort. Pharmacodynamic results suggest the immunomodulatory action of daratumumab contributes to a conducive environment for talquetamab by reducing immunosuppressive cells. Talquetamab plus daratumumab demonstrated promising efficacy outcomes in patients with heavily pretreated disease, with a safety profile consistent with each agent as monotherapy. This trial was registered at www.clinicaltrials.gov as #NCT04108195.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".