Standard-of-care idecabtagene vicleucel for relapsed/refractory multiple myeloma
Bibliographic record
Abstract
ABSTRACT: Idecabtagene vicleucel (ide-cel) was the first US Food and Drug Administration-approved chimeric antigen receptor T-cell (CAR-T) therapy for multiple myeloma (MM). However, because clinical trials are highly selective with stringent eligibility criteria, the objective of this study was to evaluate the safety and effectiveness of standard-of-care (SOC) ide-cel in the real world. Using the Center for International Blood and Marrow Transplant Research registry, we evaluated 821 patients who received SOC ide-cel. Median follow-up was 11.6 months. Median age was 66 years, and the cohort included 31% patients aged ≥70 years, with 15% Black and 7% Hispanic, and 77% of patients with ≥1 significant comorbidity. The median number of prior lines of therapy was 7, 15% patients previously received B-cell maturation antigen-directed therapy, 17% had extramedullary disease, and 27% had high-risk cytogenetics. Overall response rate was 73%, and complete response rate was 25%. Median progression-free survival was 8.8 months. Treatment-related mortality was reported in 6% of patients. Cytokine release syndrome was diagnosed in 80% of patients (grade ≥3, 3%). Immune effector cell-associated neurotoxicity syndrome was observed in 28% (grade ≥3, 5%), with no cases of Parkinsonism reported. Clinically significant infections were seen in 45% of patients. Second primary malignancies were reported in 4%, including 1% myeloid malignancies. This is, to our knowledge, the largest real-world study of ide-cel CAR-T therapy in patients with relapsed/refractory (R/R) MM. We observed a favorable safety and efficacy profile that mirrors trial experience, even in the setting of significant comorbidities in 77% of patients, many of which would have made them ineligible for the registrational KarMMa clinical trial. This trial was registered at www.clinicaltrials.gov as #NCT03361748.
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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) | 0.000 | 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".