Pivotal results of SELECT-MDS-1 phase 3 study of tamibarotene with azacitidine in newly diagnosed higher-risk MDS
Bibliographic record
Abstract
ABSTRACT: Higher-risk myelodysplastic syndrome (HR-MDS) with RARA gene overexpression is a subset of patients (pts) with an actionable target for tamibarotene, an oral and a selective retinoic acid receptor-α (RAR-α) agonist. Tamibarotene with azacitidine (AZA) showed complete remission (CR) rates in myeloid leukemia. SELECT-MDS-1 was a phase 3 study comparing the activity of tamibarotene + AZA to placebo + AZA in these pts with newly diagnosed HR-MDS with RARA overexpression. Eligible pts had confirmed RARA overexpression, untreated MDS with higher-risk features by revised International Prognostic Scoring System (IPSS-R), and marrow blast count >5%. Pts were randomized 2:1 to receive tamibarotene + AZA or placebo + AZA, respectively. A total of 246 participants were randomized with 164 and 82 in the tamibarotene + AZA and placebo + AZA groups, respectively. Baseline characteristics included: 69.9% male; median age 75 years (range, 38-93); primary MDS, 89.8%; MDS-excess blasts-1, 48% and MDS-excess blasts-2, 52%; and IPSS-R risk category intermediate (25.5%), high (35.7%), and very high (38.9%). The study did not meet the primary end point of CR, with a P value of .2084 for the treatment effect in the tamibarotene + AZA group. The CR rates were 23.81% and 18.75% in the tamibarotene + AZA and placebo + AZA groups, respectively. The use of tamibarotene-based therapy to target RAR-α as a novel approach in pts with HR-MDS with RARA gene overexpression is not a paradigm, which can augment response rates beyond AZA monotherapy. Further explorations of alternative approaches, including those with a biomarker, to alter the natural history of this disease are warranted. This trial was registered at www.clinicaltrials.gov as #NCT04797780.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".