A Multicenter Randomized Phase II Trial of Mapatumumab, a TRAIL-R1 Agonist Monoclonal Antibody, In Combination with Bortezomib In Patients with Relapsed/Refractory Multiple Myeloma (MM)
Bibliographic record
Abstract
Abstract Abstract 5031 Mapatumumab, a fully human monoclonal antibody, targets and activates the TRAIL-R1 receptor. We conducted this randomized, controlled phase II trial to evaluate the efficacy and safety of mapatumumab in combination with bortezomib in subjects with relapsed/refractory MM. Response was evaluated using the Bladé criteria. Patients were required to have a measurable serum and/or urine M-protein and have failed 1 or 2 prior therapies for MM. Patients were excluded if they had received prior bortezomib. Patients were randomly assigned to Arm A, 1.3 mg/m2 bortezomib (days 1, 4, 8, 11) every 21 days; Arm B10, bortezomib + 10 mg/kg mapatumumab (day 1) every 21 days; or Arm B20, bortezomib + 20 mg/kg mapatumumab (day 1) every 21 days. Cycles were repeated every 21 days for a maximum of 17 cycles (1 year), progressive disease or unacceptable toxicity. Subjects with complete response (CR) were treated for an additional 2 cycles after documentation of CR (not to exceed 17) and then followed. A total of 104 subjects from 4 countries were randomly assigned to the treatment arms. The addition of mapatumumab to bortezomib did not increase the response rate, progression-free survival (PFS) or duration of response compared to bortezomib alone. Adverse events were generally balanced across treatment groups; there was no evidence that mapatumumab exacerbated toxicities associated with bortezomib. As expected, the most common toxicities were hematological and peripheral neuropathies. The results do not support further evaluation of mapatumumab in combination with bortezomib in patients with advanced MM. Additional trials of mapatumumab in other indications are on-going. Arm A (n= 35) Arm B10 (n=33) Arm B20 (n=36) CR 0 0 2 PR 18 10 17 CR + PR n (%) 18 (51.4) 10 (30.3) p=0.08a 19 (52.8) p=0.91b Median PFS mo (95% CI) 8.7 (7.6, 10.0) 4.7 (2.5, 7.4) p=0.29a 5.7 (5.2, 8.9) p=0.21b Median Duration of Response mo (range) 8.5 (6.9, 14.2) 9.3 (3.9, 16.1) p=0.92a 7.6 (4.3, 8.8) p=0.41b a P value for comparison of Arm A with Arm B10 b P value for comparison of Arm A with Arm B20 Disclosures: Gallant: Human Genome Sciences, Inc.: Employment, Equity Ownership. Kumm:Human Genome Sciences, Inc.: Employment, Equity Ownership. Klein:Human Genome Sciences, Inc.: Employment, Equity Ownership.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".