A phase 2 study of carfilzomib, cyclophosphamide and dexamethasone as frontline treatment for transplant-eligible MM with high-risk features (SGH-MM1)
Bibliographic record
Abstract
The incorporation of novel agents in the treatment of MM has improved the median overall survival (OS) from 5 years to ~10 years over the last two decades [ 1 ]. However, high-risk MM patients often relapse early with poor OS despite novel therapies [ 2 ]. Managing high-risk patients with stem cell transplant, consolidation, and maintenance to achieve deep responses and minimal residual disease (MRD) negativity has been shown to improve survival irrespective of the modality used [ 3 , 4 ]. Carfilzomib is a potent irreversible proteasome inhibitor that is able to attain deep responses. Carfilzomib has been approved in the relapsed setting having demonstrated its efficacy in the ENDEAVOR and ASPIRE trials [ 5 , 6 ]. The combination of carfilzomib with cyclophosphamide in the frontline setting has been reported in transplant-ineligible patients [ 7 , 8 ] and studies are currently ongoing in the transplant-eligible setting [ 9 ]. Here, we report results from SGH-MM1, an open-label, phase 2 investigator-initiated study conducted in two tertiary centers in Singapore, which aims to explore the efficacy and safety of carfilzomib, cyclophosphamide, and dexamethasone in the frontline setting for transplant-eligible high-risk MM patients [defined as any of the following: ISS-3, del17p, t(4;14), t(14;16) or 1q21amp)]. No specific cutoffs were used in the definition of del(17p). In the seven patients with del(17p), one patient had del(17p) detected in 13.13% of 200 nuclei, whereas the rest had >50% of nuclei with del(17p). Positivity for 1q21 amplification was defined as any extra copy number of chromosome 1q21 detected on either FISH or karyotyping. In all, 27% of patients had two or more of these high-risk genetic features. This trial was registered at ClinicalTrials.gov as NCT02217163 and approved by the Institutional Review Board.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".