Asciminib demonstrates superior efficacy and safety in newly diagnosed chronic myeloid leukemia in the ASC4FIRST trial
Bibliographic record
Abstract
ABSTRACT: Many patients receiving frontline tyrosine kinase inhibitors (TKIs) for chronic-phase chronic myeloid leukemia (CML-CP) experience inadequate disease control and/or adverse events (AEs) that impair quality of life. Treatments offering optimal efficacy, safety, and tolerability will support long-term therapy. In the primary analysis from the ASC4FIRST trial, a phase 3 randomized trial comparing asciminib with investigator-selected TKIs (IS-TKIs) in newly diagnosed CML-CP, asciminib demonstrated superior efficacy vs all IS-TKIs and vs imatinib in the imatinib stratum, meeting both primary objectives. In the secondary analysis (2.2 years' median follow-up), major molecular response (MMR) rate at week 96 was 74.1% with asciminib vs 52.0% with IS-TKIs (treatment difference, 22.4% [95% confidence interval (CI), 13.6-31.3]; 1-sided P< .001) and 76.2% with asciminib vs 47.1% with imatinib in the imatinib stratum (treatment difference, 29.7% [95% CI, 17.6-41.8]; 1-sided P< .001), meeting both key secondary objectives. MMR rate was 72.0% with asciminib vs 56.9% with second-generation (2G) TKIs (treatment difference, 15.1% [95% CI, 2.3-28.0]; 1-sided P< .05), suggesting possible clinical benefit, although the study was not designed to formally confirm statistical significance for this secondary end point. Safety/tolerability remained favorable with asciminib vs IS-TKIs. Dose reductions and interruptions, respectively, occurred with asciminib (18.5%; 46.5%), imatinib (23.2%; 47.5%), and 2G TKIs (54.9%; 63.7%). The hazard ratio for time to discontinuation of treatment due to AEs for asciminib vs 2G TKIs was 0.46 (95% CI, 0.215-0.997). With longer follow-up, asciminib continued to demonstrate a favorable benefit-risk profile over IS-TKIs and imatinib, supporting its potential as a treatment option for newly diagnosed CML-CP. This trial was registered at www.clinicaltrials.gov as NCT04971226.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".