C003 | MODELING LONG-TERM PROGRESSION-FREE SURVIVAL IN TRANSPLANT-ELIGIBLE AND TRANSPLANT-INELIGIBLE NEWLY DIAGNOSED MULTIPLE MYELOMA TREATED WITH DARATUMUMAB, BORTEZOMIB, LENALIDOMIDE, AND DEXAMETHASONE
Bibliographic record
Abstract
Daratumumab, bortezomib, lenalidomide, and dexamethasone (DVRd) plus DR maintenance showed superior efficacy to VRd with R maintenance in transplant-eligible (TE) patients (pts) with newly diagnosed multiple myeloma (NDMM) in the PERSEUS trial. Similarly, the CEPHEUS trial showed superiority of DVRd vs VRd in transplant-ineligible (TIE) or transplant-deferred pts with NDMM. In the DVRd arms, median progression-free survival (PFS) was not reached (NR) at median follow-up of 47.5 months (mo; PERSEUS) and 58.7 mo (CEPHEUS); in the VRd arms, median PFS was NR in PERSEUS and was 52.6 mo in CEPHEUS. This analysis aimed to extrapolate PFS data from PERSEUS (TE) and CEPHEUS (TIE) to estimate long-term outcomes of frontline DVRd to help inform clinical decision making. Per UK NICE guidance on survival data extrapolation, 7 distributions were fitted to model PFS: exponential, Weibull, gamma, Gompertz, log-logistic, log-normal, and generalized gamma. Individual parametric curves were fit for the DVRd and VRd groups. Extrapolations were capped by UK population data (2020–2022) on disease-specific and all-cause mortality, using median population age and the proportion of males in the cohort at treatment initiation. PFS projections begin at the median population age. In PERSEUS, 709 TE pts were randomized (DVRd, n=355; VRd, n=354; median age, 60 yrs; 59% male). In CEPHEUS, 289 TIE pts were randomized (DVRd, n=144; VRd, n=145; median age, 72 yrs; 51% male). At 48 mo, Kaplan-Meier estimates of PFS in PERSEUS TE pts were 84.3% vs 67.7% for DVRd and VRd, respectively; in CEPHEUS TIE pts, they were 72.3% vs 52.3% (Figure). Based on modeling in PERSEUS TE pts, estimated median PFS was 158–255 mo (13.2–21.2 yrs) for DVRd and 76–119 mo (6.3–9.9 yrs) for VRd. Exponential distribution (best fit) gave PFS estimates of 205 vs 87 mo (17.1 vs 7.3 yrs) for DVRd and VRd, respectively. In CEPHEUS TIE pts, estimated median PFS was 96–118 mo (8.0–9.8 yrs) for DVRd and 52–54 mo (4.3–4.5 yrs) for VRd. Exponential distribution gave PFS estimates of 100 vs 53 mo (8.3 vs 4.4 yrs) for DVRd and VRd, respectively. PFS projections were significantly longer with DVRd vs VRd in both TE and TIE pts with NDMM. As expected, projected PFS with DVRd was longer for TE (205 mo from baseline age of 60 yrs) vs TIE (100 mo from age 72 yrs). These extrapolations support DVRd use beyond observed PFS data, helping to reinforce the benefit of DVRd with daratumumab-containing maintenance in all pts with NDMM.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.005 | 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".