Real-World Experience with CPX-351 for Secondary Acute Myeloid Leukemia: Comparison with FLAG-IDA in a Propensity Score Matching Analysis
Bibliographic record
Abstract
CPX-351 is approved for therapy-related acute myeloid leukemia (t-AML), and AML with myelodysplastic-related changes (AML-MRC). This approval was based on improved survival, remission rates, and similar safety compared to 7+3 regimen. In clinical practice, FLAG-IDA, followed by Allogenic Stem Cell transplant (ASCT) is an acceptable approach for this group of patients (pts). Evaluating real-world data on CPX compared to FLAG-IDA, and identifying which pts might benefit most from either treatment, is crucial for optimizing treatment decisions. Aims To report real-world outcomes of CPX vs FLAG-IDA in terms of Overall Survival (OS), Leukemia-free Survival (LFS), and complete remission (CR), and to determine if mutational profiles can predict responses. Methods Patients aged 18+ meeting WHO criteria for t-AML and AML-MRC with next-generation sequencing (NGS) profiles were included. Data were collected from 10 Canadian centers for CPX and the Princess Margaret Cancer Centre for FLAG-IDA. A total of 76 patients treated with CPX and 95 with FLAG-IDA were identified. Propensity Score Matching (PSM) was used to adjust for baseline differences between the two treatment groups. Key pre-treatment variables included: age, complex cytogenetics, and TP53 mutational status. PSM resulted in 92 pts (46 case-control pairs) with a caliper difference within 0.2. Results Significant differences between pts treated with different approaches were mitigated when PSM was applied. The median number of frequently detected somatic mutations was 2 (range: 1-8), with the most common mutations being RUNX1 (n=19), ASXL1 (n=20), DNMT3A (n=20), and TET2 (n=18). In the PSM-selected population (n=92), the median follow-up time was 303 days (range: 22-1488). CR rates were higher with FLAG-IDA, with CR achieved in 27 (61%) pts treated with CPX-351 compared to 38 (82%) pts treated with FLAG-IDA (p=0.024). This finding did not translate into significantly higher rates of ASCT. Overall, 18 (41%) pts in the CPX group and 24 (52%) pts in the FLAG-IDA group proceeded with ASCT (p=0.28), corresponding to 55% and 52% of the pts who achieved CR1 after first induction (p=0.81). Assessment of mutations and their biological pathways showed that pts with ASXL1 mutations had higher CR rates with FLAG-IDA (90%) compared to CPX (50%) (p=0.046). Activating signaling (AS) mutations also showed better CR rates with FLAG-IDA (100%) vs. CPX (70%) (p=0.04). The overall 1-year OS was 52.2% (95% CI: [40.5-62.6]). There were no significant differences in outcomes when comparing CPX with FLAG-IDA. For pts treated with CPX, the 1-year OS was 56.4% [39.6-70.2], compared to 49.4% [33.3-63.5] for those treated with FLAG-IDA (p=0.73, HR: 1.10 [0.60-2.1]). The 1-year LFS was 40% [25.6-55.4] for the CPX-351 group and 46.30% [30.8-60.5] for the FLAG-IDA group (p=0.59, HR: 0.86, [0.50-1.5]. When censoring OS for transplant, the 1-year OS was 52.8% [32.0-69.9] for CPX and 47.8% [23.9-68.4] for FLAG-IDA (p=0.55, HR: 0.79 [0.37-1.7]. Pts who underwent ASCT had significantly better OS (p=0.003). However, there was no significant OS difference between ASCT preceded by FLAG-IDA or CPX(p=0.08). Specifically, for pts who had ASCT, the 1-year OS was 78% [47.0-92.7] for CPX and 58% [35.0-75.9] for FLAG-IDA. Considering pts characteristics, type of mutations, or biological pathways involved, the only subgroup that demonstrated a difference in OS when comparing CPX with FLAG-IDA was the presence of tumor suppressor gene mutations (TS=TP53+PHF6, n=17). Pts with these mutations showed higher survival in the uni and multivariable analysis when treated with CPX; the 1-year survival rate for pts treated with CPX was 25% [3.7-55.8], compared to 13% [0.7-44] for those treated with FLAG-IDA (HR 3.11 [1.4-6.9], p<0.001). No other factors showed significant differences between treatments. Conclusions We used PSM to effectively minimize differences in pts characteristics. Although FLAG-IDA was associated with higher CR rates, particularly in pts with ASXL1 mutations and, AS mutations, this did not translate into higher ASCT rates, improved OS or LFS. The only subgroup that showed a difference in OS in favor of CPX was the one with TS gene mutations.These results should be interpreted with caution due to the small pt numbers. Data regarding the reasons for not proceeding with ASCT were not available. Future research will focus on expanding the cohort and evaluating adverse events
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".