Bortezomib retreatment for relapsed and refractory multiple myeloma in real‐world clinical practice
Bibliographic record
Abstract
AIMS: OBservational Study (eVOBS) study assessed bortezomib-based therapies for patients with MM in everyday practice. Here, we report on those patients receiving retreatment with bortezomib. METHODS: Consenting adults scheduled to receive bortezomib for MM were enrolled at 162 sites across Europe, Canada, Brazil, Russia, and Turkey between 2006 and 2010. Retrospective data on prior therapies and prospective observational data after bortezomib initiation were captured electronically at baseline, after every bortezomib cycle, and every 12 weeks after discontinuation or progression. Investigator-assessed responses and adverse events (AEs) were evaluated. RESULTS: Ninety-six of 873 patients enrolled to eVOBS received bortezomib as first retreatment for progressive disease during the prospective observation period. Median age was 62 years, 53% were male, and median number of prior therapies at retreatment was 4. Overall, 41% of patients initiated bortezomib retreatment in combination with dexamethasone, 16% in combination with lenalidomide, and 21% received monotherapy. Rate of partial response or better (≥PR) was 75% at initial bortezomib therapy, including 44% complete response (CR)/near CR (nCR); at retreatment, ≥PR rate was 46%, including 15% CR/nCR. Median progression-free survival was 11.4 months (95% confidence interval [CI]: 9.1-12.7) from start of initial bortezomib treatment and 6.4 months (95% CI: 4.4-7.2) from start of retreatment. Median overall survival from start of retreatment was 17.6 months (95% CI: 14.4-23.5). Of the 96 patients retreated with bortezomib, 77% reported an AE. Peripheral neuropathy during bortezomib retreatment occurred in 49% of patients, including 10% grade 3/4. CONCLUSION: These data suggest that retreatment with bortezomib is a feasible option for patients with relapsed/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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".