c‐MYC expression and maturity phenotypes are associated with outcome benefit from addition of ixazomib to lenalidomide‐dexamethasone in myeloma
Bibliographic record
Abstract
OBJECTIVES: In the TOURMALINE-MM1 phase 3 trial in relapsed/refractory multiple myeloma, ixazomib-lenalidomide-dexamethasone (IRd) showed different magnitudes of progression-free survival (PFS) benefit vs placebo-Rd according to number and type of prior therapies, with greater benefit seen in patients with >1 prior line of therapy or 1 prior line of therapy without stem cell transplantation (SCT). METHODS: RNA sequencing data were used to investigate the basis of these differences. RESULTS: The PFS benefit of IRd vs placebo-Rd was greater in patients with tumors expressing high c-MYC levels (median not reached vs 11.3 months; hazard ratio [HR] 0.42; 95% CI, 0.26, 0.66; P < .001) compared with in those expressing low c-MYC levels (median 20.6 vs 16.6 months; HR 0.75; 95% CI, 0.42, 1.2). Expression of c-MYC in tumors varied based on the number and type of prior therapy received, with the lowest levels observed in tumors of patients who had received 1 prior line of therapy including SCT. These tumors also had higher expression levels of CD19 and CD81. CONCLUSIONS: PFS analyses suggest that lenalidomide and ixazomib target tumors with different levels of c-MYC, CD19, and CD81 expression, thus providing a potential rationale for the differential benefits observed in the TOURMALINE-MM1 study. This trial was registered at www.clinicaltrials.gov as: NCT01564537.
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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) | 0.000 | 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 | 0.001 |
| 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".