A phase 1/2 of carfilzomib and melphalan conditioning for autologous stem cell transplantation for multiple myeloma (<scp>CARAMEL</scp>)
Bibliographic record
Abstract
Abstract In this phase 1/2 study, carfilzomib was added to high‐dose melphalan conditioning prior to autologous stem cell transplantation (ASCT) in patients with multiple myeloma that had been treated with ≤2 prior lines of therapy. Carfilzomib was escalated at doses of 27, 36, 45, and 56 mg/m2 on days −6, −5, −2, and −1 before ASCT in the phase 1 component of the study. In addition, all the patients received melphalan 100 mg/m2 on days −4 and −3. The primary endpoint of the phase 1 component was to identify the maximum tolerated dose, and the primary endpoint of the phase 2 component was the rates of complete response (≥CR) at 1 year after ASCT. The phase 1 dose escalation cohort included 14 patients, and 35 patients were included in the phase 2 cohort. The maximum tested dose was 56 mg/m2 (MTD). The median time from diagnosis to study enrollment was 5.8 (range 3.4–88.4) months, and 16% of patients had obtained a ≥CR prior to ASCT. The best response within 1 year after ASCT was a ≥ CR rate in 22% for the entire cohort, and 22% for patients treated at the MTD. The ≥VGPR rates improved from 41% before ASCT to 77% by 1 year after ASCT. One patient had a grade 3 renal adverse event, and renal function returned to baseline with supportive care. The rate of grade 3–4 cardiovascular toxicity was 16%. The addition of carfilzomib to melphalan conditioning was safe and resulted in deep responses after ASCT.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".