Asciminib vs bosutinib in chronic-phase chronic myeloid leukemia previously treated with at least two tyrosine kinase inhibitors: longer-term follow-up of ASCEMBL
Bibliographic record
Abstract
Asciminib, the first BCR::ABL1 inhibitor that Specifically Targets the ABL Myristoyl Pocket (STAMP), is approved worldwide for the treatment of adults with Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase (CML-CP) treated with ≥2 prior tyrosine kinase inhibitors (TKIs). In ASCEMBL, patients with CML-CP treated with ≥2 prior TKIs were randomized (stratified by baseline major cytogenetic response [MCyR]) 2:1 to asciminib 40 mg twice daily or bosutinib 500 mg once daily. Consistent with previously published primary analysis results, after a median follow-up of 2.3 years, asciminib continued to demonstrate superior efficacy and better safety and tolerability than bosutinib. The major molecular response (MMR) rate at week 96 (key secondary endpoint) was 37.6% with asciminib vs 15.8% with bosutinib; the MMR rate difference between the arms, after adjusting for baseline MCyR, was 21.7% (95% CI, 10.53-32.95; two-sided p = 0.001). Fewer grade ≥3 adverse events (AEs) (56.4% vs 68.4%) and AEs leading to treatment discontinuation (7.7% vs 26.3%) occurred with asciminib than with bosutinib. A higher proportion of patients on asciminib than bosutinib remained on treatment and continued to derive benefit over time, supporting asciminib as a standard of care for patients with CML-CP previously treated with ≥2 TKIs.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".