A phase 2, randomized, double‐blind, placebo‐controlled study of siltuximab (anti‐IL‐6 mAb) and bortezomib versus bortezomib alone in patients with relapsed or refractory multiple myeloma
Bibliographic record
Abstract
We compared the safety and efficacy of siltuximab (S), an anti-interleukin-6 chimeric monoclonal antibody, plus bortezomib (B) with placebo (plc) + B in patients with relapsed/refractory multiple myeloma in a randomized phase 2 study. Siltuximab was given by 6 mg/kg IV every 2 weeks. On progression, B was discontinued and high-dose dexamethasone could be added to S/plc. Response and progression-free survival (PFS) were analyzed pre-dexamethasone by European Group for Blood and Marrow Transplantation (EBMT) criteria. For the 281 randomized patients, median PFS for S + B and plc + B was 8.0 and 7.6 months (HR 0.869, P = 0.345), overall response rate was 55 versus 47% (P = 0.213), complete response rate was 11 versus 7%, and median overall survival (OS) was 30.8 versus 36.8 months (HR 1.353, P = 0.103). Sustained suppression of C-reactive protein, a marker reflective of inhibition of interleukin-6 activity, was seen with S + B. Siltuximab did not affect B pharmacokinetics. Siltuximab/placebo discontinuation (75 versus 66%), grade ≥3 neutropenia (49 versus 29%), thrombocytopenia (48 versus 34%), and all-grade infections (62 versus 49%) occurred more frequently with S + B. The addition of siltuximab to bortezomib did not appear to improve PFS or OS despite a numerical increase in response rate in patients with relapsed or refractory multiple myeloma.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".