Daratumumab plus lenalidomide and dexamethasone in transplant-ineligible newly diagnosed multiple myeloma: frailty subgroup analysis of MAIA
Bibliographic record
Abstract
Abstract In the phase 3 MAIA study of patients with transplant-ineligible newly diagnosed multiple myeloma (NDMM), daratumumab plus lenalidomide/dexamethasone (D-Rd) improved progression-free survival (PFS) versus lenalidomide/dexamethasone (Rd). We present a subgroup analysis of MAIA by frailty status. Frailty assessment was performed retrospectively using age, Charlson comorbidity index, and baseline Eastern Cooperative Oncology Group performance status score. Patients were classified as fit, intermediate, non-frail (fit + intermediate), or frail. Of the randomized patients (D-Rd, n = 368; Rd, n = 369), 396 patients were non-frail (D-Rd, 196 [53.3%]; Rd, 200 [54.2%]) and 341 patients were frail (172 [46.7%]; 169 [45.8%]). After a 36.4-month median follow-up, non-frail patients had longer PFS than frail patients, but the PFS benefit of D-Rd versus Rd was maintained across subgroups: non-frail (median, not reached [NR] vs 41.7 months; hazard ratio [HR], 0.48; P < 0.0001) and frail (NR vs 30.4 months; HR, 0.62; P = 0.003). Improved rates of complete response or better and minimal residual disease (10 –5 ) negativity were observed for D-Rd across subgroups. The most common grade 3/4 treatment-emergent adverse event in non-frail and frail patients was neutropenia (non-frail, 45.4% [D-Rd] and 37.2% [Rd]; frail, 57.7% and 33.1%). These findings support the clinical benefit of D-Rd in transplant-ineligible NDMM patients enrolled in MAIA, regardless of frailty status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".