A comparison of real-world outcomes of asciminib versus ATP-competitive tyrosine kinase inhibitors as second-line treatment in patients with chronic myeloid leukemia in chronic phase
Bibliographic record
Abstract
Abstract Introduction: Adenosine triphosphate (ATP)-competitivetyrosine kinase inhibitors (TKIs) are part of the current treatment landscape for Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase (CML-CP), approved by the FDA between 2006–2012 for newly diagnosed and previously-treated patients. Asciminib, a TKI that targets the ABL myristoyl pocket, received FDA approval in October 2024 for treatment of newly diagnosed or previously treated CML-CP following 2021 approval for third-line treatment or for those with T315I mutation. This study aimed to compare real-world outcomes of patients treated with asciminib versus ATP-competitive TKIs as second-line treatment (2L). Methods: This retrospective panel-based chart review study collected de-identified patient data via an online case report form between February-December 2024 (asciminib cohort), and May-June 2025 (comparison cohort) from eligible US oncologists and hematologists with experience treating CML. Adult patients with CML-CP were included if they had no T315I mutation and initiated asciminib (asciminib cohort) or a 1st- or 2nd-generation ATP-competitive TKI (comparison cohort) from January 2022–June 2023 (index) as 2L. Entropy balancing was used to adjust baseline characteristics between the two cohorts including demographics (age, sex, race/ethnicity, index year), severity at diagnosis (ECOG PS, Sokal score), first-line (1L) TKI characteristics (1st- or 2nd-generation TKI, reason for 1L TKI termination, last response on 1L TKI), and comorbidity profile at index (NCI comorbidity index). Time to discontinuation, and time to BCR::ABL1≤0.1% (MR3 or better) and BCR::ABL1≤0.01% (MR4 or better) were assessed using weighted Kaplan-Meier analyses; Wilcoxon tests were reported. Data collection is ongoing for the comparison cohort. Results: A total of 255 patients were included in the asciminib cohort, and an interim sample of 137 patients comprised the comparison cohort (dasatinib: 43.8%, nilotinib: 32.1%, bosutinib: 20.4%, imatinib: 3.6%). Data were collected from 76 physicians (community practice: 47.4%, academic center: 52.6%) for the asciminib cohort and 33 physicians (community: 36.4%, academic: 63.6%) for the comparison cohort, similarly distributed across all US census regions. After balancing, characteristics were similar between the asciminib and comparison cohorts, including median age (62.0 vs 62.0), proportion female (43.5% vs 43.8%), race/ethnicity (white: 56.1% vs 56.2%, black: 20.8% vs 20.4%), ECOG ≥2 (17.3% vs 17.5%), intermediate-high Sokal scores (76.1% vs 75.9%), and NCI comorbidity index >0 (60.0% vs 59.9%). Similar proportions of patients discontinued their 1L TKI due to intolerance (43.5% vs 43.8%) or lack of efficacy (42.4% vs 42.3%) and had a last response of MR3 or better on 1L (28.2% vs 28.5%). All standardized mean differences were ≤0.01. By 48-week post-index, 68.3% of the asciminib vs 58.1% of the comparison cohort achieved or maintained MR3 (p<0.05); and 40.6% vs 21.0% achieved or maintained MR4 (p<0.05). Median time to MR3 (MR4) was 30.7 (59.7) and 39.7 (74.0) weeks for the asciminib and comparison cohorts, respectively. By 48-week post-index, 4.6% of the asciminib vs 13.0% of the comparison cohort had discontinued treatment for any reason (p<0.05). During that period, discontinuation due to intolerance occurred in 1.6% of patients in the asciminib vs 3.6% in the comparison cohort, and discontinuation due to resistance was observed in none and 4.4% of patients, respectively. Moreover, post-index, intolerance led to temporary treatment interruption in 4.3% of patients in the asciminib vs 8.8% in the comparison cohort, and to dose reduction in 2.0% and 5.8% of patients, respectively. Dose increase due to resistance was reported only in the comparison cohort, for 5.1% of patients.Conclusions: Patients with CML-CP who received asciminib as 2L achieved deeper and faster molecular responses, with higher rates of MR3 and MR4 and shorter time to MR3, in comparison to those treated with ATP-competitive TKIs. Moreover, asciminib-treated patients experienced fewer dose adjustments and discontinuations due to intolerance or resistance similar to previously reported data from ASC4FIRST and ASCEMBL. Findings from this large real-world study suggest that asciminib offers favorable tolerability and better efficacy compared to ATP-competitive TKIs in patients with CML-CP as 2L in the US clinical practice.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".