High response rate to bortezomib with or without dexamethasone in patients with relapsed or refractory multiple myeloma: results of a global phase 3b expanded access program
Bibliographic record
Abstract
Phase 2 trials have demonstrated that bortezomib +/- dexamethasone is safe and effective in relapsed multiple myeloma (MM). In this multicentre, open-label, phase 3b trial, 638 patients with relapsed or refractory MM (median 3 prior therapies) received bortezomib 1.3 mg/m2 on days 1, 4, 8, and 11 of a maximum of eight 3-week cycles (median 5 cycles). Dexamethasone 20 mg/d was added the day of and day after each bortezomib dose for progressive disease after > or =2 cycles or for stable disease after > or =4 cycles. Responses were assessed based on M-protein changes. Overall response rate was 67%, including 11% complete (100% M-protein reduction), 22% very good partial (75-99% reduction), 18% partial (50-74% reduction), and 16% minimal response (25-49% reduction). Dexamethasone was added in 208 patients (33%), of whom 70 (34%) showed improved response. Median time to best response of minimal response or better was 84 d. Most common grade 3/4 adverse events were thrombocytopenia (39%), neutropenia (16%), anaemia (12%), diarrhoea (7%), and peripheral neuropathy (6%). Neuropathy (any grade) was seen in 25% of the patients and led to discontinuation in 5%. Bortezomib, alone and combined with dexamethasone, is safe and effective in heavily pretreated patients with relapsed or refractory MM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".