Bortezomib Therapy Response Is Independent of Cytogenetic Abnormalities in Relapsed/Refractory Multiple Myeloma.
Bibliographic record
Abstract
Abstract Myeloma patients with unfavorable molecular cytogenetics have a poor prognosis irrespective of treatment with conventional chemotherapy or autologous stem cell transplant. To investigate whether bortezomib, a new proteasome inhibitor, is active in relapsed/refractory myeloma patients with genetic risk factors, we evaluated the outcome of 65 patients and correlated the clinical response with 13q deletion, translocations t(11;14) and t(4;14) and CKS1B amplification as detected by interphase cytoplasmic fluorescence in situ hybridization (cIg-FISH). Thirty-seven of 61 (61%) evaluable patients had an objective response to bortezomib with median progression free (PFS) and overall survivals (OS) of 9.5 and 15.1 months, respectively. Of 43 cases with evaluable bone marrows, cIg-FISH determination of del(13q), t(4;14), t(11;14) and CKS1B amplification was done on 40, 41, 41 and 37 cases and the frequency of their detection was 35%, 15%, 15%, and 32% respectively. Two different abnormalities coexisted in 12 patients: 13q deletion with CKS1B amplification in 7, t(11;14) with CKS1B amplification in 2, t(4;14) with CKS1B amplification in 1, 13q deletion with t(11;14) in 1 and 13q deletion with t(4;14) in 1 patient. There was no statistically significant difference in response to bortezomib for patients with or without 13q deletion (77% vs. 50%), t(4;14) (67% vs. 56%), t(11;4) (33% vs. 62%), or CKS1B amplification (67% vs. 57%). Furthermore, there was no statistically significant difference in PFS or OS following bortezomib therapy between patients with or without these molecular cytogenetic abnormalities. Our data suggest that, in this pilot study, bortezomib is an effective salvage therapy for refractory/relapsed myeloma, irrespective of genetic risk factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".