KarMMa-RW: A study of real-world treatment patterns in heavily pretreated patients with relapsed and refractory multiple myeloma (RRMM) and comparison of outcomes to KarMMa.
Bibliographic record
Abstract
8525 Background: RRMM patients (pts) triple-class exposed (to immunomodulatory drugs [IMiDs], proteasome inhibitors [PIs] and anti-CD38 monoclonal antibodies [mAbs]) have limited treatment (tx) options. The ongoing phase II KarMMa study (NCT03361748) is examining idecabtagene vicleucel (ide-cel; bb2121), a BCMA targeted CAR T cell therapy, in RRMM pts with ≥3 prior regimens (IMiD, PI and CD38 mAb inclusive) who are refractory to their last tx per IMWG criteria. This study aimed to 1) assess tx patterns and outcomes in real world (RW) RRMM pts similar to the KarMMa population and; 2) compare outcomes with SoC in a synthetic cohort vs ide-cel in KarMMa. Methods: In this global, noninterventional, retrospective study (KarMMa-RW), pt-level data from clinical sites, registries and databases were collated into a single data model. RW pts meeting KarMMa eligibility criteria (eligible cohort; EC) were compared with KarMMa (N = 128) using trimmed stabilized inverse probability of tx weighted propensity scores (IPTW PS) for pts in both studies with Poisson regression for ORR and ≥VGPR, and Cox models with study as a term for PFS. All models were adjusted for unbalanced covariates. Results: Of 1949 RW pts, 1171 were refractory to last regimen (median age, 68 y; median no. of prior regimens, 5; triple-class refractory, 41%). Further selection for subsequent tx, organ function and no comorbidities yielded 190 EC pts who had > 90 distinct tx regimens. With a median follow-up of 11.3 mo (KarMMa) and 10.2 mo (EC) at data cutoff (Oct 30, 2019), ORR, ≥VGPR and PFS were significantly improved in KarMMa vs EC (Table). Conclusions: Results from the KarMMa-RW study confirm that there is no clear SoC for heavily pretreated RW RRMM pts and responses are suboptimal with currently available therapies. Ide-cel showed deep, durable responses and significantly improved PFS in RRMM pts, representing a potential new tx option in RRMM. Clinical trial information: tbd . [Table: see text]
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".