Improved long-term tolerability with asciminib (ASC) vs investigator-selected (IS) tyrosine kinase inhibitors (TKIs) in patients (pts) with newly diagnosed chronic myeloid leukemia in chronic phase (CML-CP): Week 96 exploratory analysis of the phase 3 ASC4FIRST trial
Bibliographic record
Abstract
Abstract Introduction Long-term CML treatment (Tx) requires assessing adverse event (AE) burden over time to optimize safety, tolerability, and efficacy. ASC4FIRST (NCT04971226) results demonstrated superior efficacy and favorable safety/tolerability of ASC vs IS-TKIs in newly diagnosed CML-CP. A prior report showed a lower risk of discontinuation due to AEs with ASC vs second-generation (2G) TKIs in a time to Tx discontinuation due to AEs (TTDAE) analysis (hazard ratio, 0.46; 95% CI, 0.215-0.997), suggesting better tolerability with ASC. We report exploratory post hoc analyses, including an innovative analysis of AE-free days, further evaluating the tolerability of ASC vs IS-TKI (imatinib [IMA]/2G TKIs) by the wk 96 analysis cutoff (Oct 22, 2024). Methods Adults with newly diagnosed CML-CP were randomized 1:1 to receive ASC or IS-TKI (at label dose), stratified by ELTS risk category and prerandomization IS-TKI (IMA/2G TKIs). Dose modifications occurred per protocol for ASC and at investigator's discretion for IS-TKIs. All reported AEs occurred on Tx or ≤30 days after last dose. Exploratory tolerability analyses included frequency/grade/type of AEs; relative dose intensity; rate of dose adjustment, interruption, or discontinuation; percentage of AE-free days (number of days pt was on Tx without any-grade AEs divided by Tx duration in days, censored at the wk 96 visit; a value of 100% indicates no AEs were experienced on Tx); and pt-reported outcome (PRO) measures (PRO-CTCAE and FACIT GP5). Results Safety analyses included all pts who received Tx in IMA (ASCIMA [n=100]; IS-TKIIMA [n=99]) and 2G TKI (ASC2G [n=100]; IS-TKI2G [n=102]) strata. Median follow-up was similar across groups (ASCIMA [25.1 mo]; IS-TKIIMA [24.3 mo]; ASC2G [28.2 mo]; IS-TKI2G [27.7 mo]). More pts were continuing Tx at cutoff with ASCIMA (83.0%) vs IS-TKIIMA (52.5%) and ASC2G (81.0%) vs IS-TKI2G (69.6%). More pts had relative dose intensity of >90% with ASCIMA (86.0%) vs IS-TKIIMA (79.8%) and ASC2G (88.0%) vs IS-TKI2G (68.6%). The proportion of pts with dose reductions was lower with ASCIMA (n=19, 19.0%) vs IS-TKIIMA (n=23, 23.2%) and ASC2G (n=18, 18.0%) vs IS-TKI2G (n=56, 54.9%). A similar number of pts with ASCIMA (47.0%) vs IS-TKIIMA (47.5%) and fewer pts with ASC2G (46.0%) vs IS-TKI2G (63.7%) had dose interruptions for any reason (included AEs, dosing/dispensing error, physician/pt decision, and technical problems); interruptions due to AEs were fewer with ASC vs IS-TKIs (ASCIMA [33.0%] vs IS-TKIIMA [37.4%]; ASC2G [33.0%] vs IS-TKI2G [51.0%]). Less pts with ASC vs IS-TKIs had dose adjustment and/or interruption (ASCIMA [13.0%] vs IS-TKIIMA [18.2%]; ASC2G [14.0%] vs IS-TKI2G [31.4%]) and discontinuation (ASCIMA [3.0%] vs IS-TKIIMA [6.1%]; ASC2G [1.0%] vs IS-TKI2G [7.8%]) due to grade 1/2 nonhematologic AEs, most common (≥3%) being diarrhea, fatigue, COVID-19, nausea, and pleural effusion. A lower proportion of pts with ASC vs IS-TKIs discontinued due to grade ≥3 nonhematologic AEs (ASCIMA [2.0%] vs IS-TKIIMA [4.0%]; ASC2G [2.0%] vs IS-TKI2G [3.9%]). Dose adjustment and/or interruption due to grade ≥3 nonhematologic AEs occurred in 17.0% vs 8.1% of pts with ASCIMA vs IS-TKIIMA and 11.0% vs 17.6% with ASC2G vs IS-TKI2G. Pts with ASC vs IS-TKIs had a higher median percentage of AE-free days by wk 96 (ASCIMA [15.7%] vs IS-TKIIMA [3.5%]; ASC2G [22.6%] vs IS-TKI2G [4.3%]) and vs individual 2G TKIs (nilotinib [13.5%]; dasatinib [4.2%]; bosutinib [0.1%]) in this arm. Pts with ASC had a higher proportion of symptomatic (nonhematologic, nonlaboratory AEs) AE–free days (ASCIMA [31.2%] vs IS-TKIIMA [9.9%]; ASC2G [34.2%] vs IS-TKI2G [15.7%]; and vs individual 2G TKIs: nilotinib [30.3%]; dasatinib [8.5%]; bosutinib [0.1%]). When analyzing maximum scores in PRO-CTCAE reported from baseline to wk 96, symptoms reported with ASC vs IS-TKIs were generally less frequent and less severe, with a smaller impact on daily life. At wk 96, more pts reported being not at all bothered by Tx side effects with ASC vs IS-TKIs per FACIT GP5 (67.0% vs 46.1%). Conclusions Pts with ASC had more days free from AEs, especially symptomatic AEs, and reported a lower symptom burden. Effective relative dose intensity (>90%) was higher with ASC vs IS-TKIs, with generally fewer pts requiring dose reduction, interruption, or discontinuation. These results from ASC4FIRST further support ASC’sfavorable tolerability vs all current frontline 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.003 | 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".