A phase 3, open-label, randomized study of asciminib, a STAMP inhibitor, vs bosutinib in CML after 2 or more prior TKIs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patients with chronic myeloid leukemia in chronic phase (CML-CP) resistant/intolerant to ≥2 tyrosine kinase inhibitors (TKIs) are at high risk of experiencing poor outcomes because of disease biology and inadequate efficacy and/or safety of current therapies. Asciminib, a first-in-class BCR-ABL1 inhibitor Specifically Targeting the ABL Myristoyl Pocket (STAMP), has the potential to overcome resistance/intolerance to approved TKIs. In this phase 3, open-label study, patients with CML-CP previously treated with ≥2 TKIs were randomized (2:1) to receive asciminib 40 mg twice daily vs bosutinib 500 mg once daily. Randomization was stratified by major cytogenetic response (MCyR) status at baseline. The primary objective was to compare the major molecular response (MMR) rate at week 24 for asciminib vs bosutinib. A total of 233 patients were randomized to asciminib (n = 157) or bosutinib (n = 76). Median follow-up was 14.9 months. The MMR rate at week 24 was 25.5% with asciminib and 13.2% with bosutinib. The difference in MMR rate between treatment arms, after adjusting for MCyR at baseline, was 12.2% (95% confidence interval, 2.19-22.30; 2-sided P = .029). Fewer grade ≥3 adverse events (50.6% vs 60.5%) and adverse events leading to treatment discontinuation (5.8% vs 21.1%) occurred with asciminib than with bosutinib. The study showed a superior efficacy of asciminib compared with that of bosutinib, together with a favorable safety profile. These results support the use of asciminib as a new therapy in patients with CML-CP who are resistant/intolerant to ≥2 prior TKIs. This trial was registered at www.clinicaltrials.gov as #NCT03106779.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it