Impact of prior therapy on efficacy and safety of oral ixazomib-lenalidomide-dexamethasone (IRd) vs placebo-Rd in patients (pts) with relapsed/refractory multiple myeloma (RRMM) in TOURMALINE-MM1.
Bibliographic record
Abstract
8039 Background: TOURMALINE-MM1 (NCT01564537) demonstrated improved PFS with IRd vs placebo-Rd (median 20.6 vs 14.7 mos; HR 0.74) in pts with RRMM after at least 1 prior therapy (Moreau et al, ASH 2015). Efficacy and safety of IRd vs placebo-Rd were analyzed according to prior proteasome inhibitor (PI) and prior thalidomide (thal)/lenalidomide (R) exposure. Methods: Pts were randomized 1:1 to receive IRd or placebo-Rd until disease progression or unacceptable toxicity. Pts with prior PI- and thal/R-based regimens, and pts refractory to thal, were eligible, but not pts refractory to PI- or R-based prior therapy. Results: Of 722 pts, 69% had prior PI therapy (< 1% prior carfilzomib) and 55% had prior thal/R therapy, including 45% prior thal (12% thal-refractory) and 12% prior R. Prior therapies were balanced between arms. At the primary analysis (median follow-up ~15 mos), consistent PFS benefit was seen with IRd regardless of prior PI or thal/R exposure (Table). CR+VGPR rates with IRd vs placebo-Rd appeared generally similar in PI-naïve (54% vs 37%), PI-exposed (46% vs 40%), thal/R-naïve (51% vs 44%), thal/R-exposed (45% vs 35%), R-naïve (48% vs 39%), and R-exposed (45% vs 36%) pts, but lower in thal-refractory (30% vs 27%) pts. At a 23-mos analysis, IRd safety profile was consistent regardless of prior PI or thal/R exposure; rates of grade ≥ 3 AEs with IRd vs placebo-Rd were 76% vs 66% in PI-naïve, 73% vs 70% in PI-exposed, 75% vs 71% in thal/R-naïve, and 73% vs 67% in thal/R-exposed pts. Conclusions: The benefit of IRd vs placebo-Rd appeared consistent across subgroups defined by prior PI and thal/R exposure, with a consistent safety profile with IRd. Clinical trial information: NCT01564537.Median PFS, mos. Subgroup IRd, N = 360 Placebo-Rd, N = 362 HR PI naïve (n = 110 vs 109) NE 15.7 0.75 Bortezomib (Btz) naïve (n = 112 vs 112) NE 15.9 0.75 PI exposed (n = 250 vs 253) 18.4 13.6 0.74 Btz exposed (n = 248 vs 250) 18.5 13.6 0.75 Thal/R naïve (n = 167 vs 158) 20.6 13.6 0.70 R (n = 316 vs 318) / Thal naïve (n = 203 vs 192) 20.6/20.6 13.6/13.6 0.77/0.69 Thal/R exposed (n = 193 vs 204) NE 17.5 0.74 R exposed (n = 44 vs 44) NE 17.5 0.58 Thal exposed (n = 157 vs 170) / refractory (n = 40 vs 49) NE/16.6 15.7/13.0 0.75/0.73
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".