A Phase 1 Study of Mapatumumab (Fully Human Monoclonal Antibody to TRAIL-R1) in Patients with Advanced Solid Malignancies
Bibliographic record
Abstract
PURPOSE: Mapatumumab (TRM-1, HGS-ETR1) is a fully human agonistic monoclonal antibody that targets and activates tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) receptor 1 (death receptor 4). Mapatumumab functions like the natural receptor ligand, TRAIL, a tumor necrosis factor superfamily member that is an important mediator of apoptosis in cancer cell lines. Promising preclinical activity with mapatumumab has been observed. EXPERIMENTAL DESIGN: This phase I, open-label, dose-escalation study assessed the tolerability and toxicity profile of > or =2 doses of mapatumumab administered i.v. in patients with advanced solid tumors. Patients received mapatumumab every 28 days until progression or dose-limiting toxicity. RESULTS: There were escalation levels from 0.01 to 20.0 mg/kg. Forty-one patients, 27 female, with a median age of 55 years (range, 23-81) were entered into the study and received 143 courses. The most common diagnoses were colorectal (10 patients) and ovarian cancer (9 patients). Patients received a median of two cycles (range, 1-33). Mapatumumab was well tolerated. Adverse events considered at least possibly related to mapatumumab that occurred most frequently included fatigue (36.2%), hypotension (34.1%), nausea (29.3%), and pyrexia (12.2%). The majority of adverse events were grade 1 or 2. The maximum tolerated dose was not reached. Linear pharmacokinetics was observed for doses up to 0.3 mg/kg and for the 20 mg/kg level, whereas exposure at 3 and 10 mg/kg increased less than proportionally. No objective responses were observed, but 12 patients had stable disease for 1.9 to 29.4 months. CONCLUSIONS: Mapatumumab is well tolerated and further evaluation of this TRAIL-R1 targeting agent is warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".