Therapy-related core binding factor Acute Myeloid Leukemia – a Study of the french acute leukemia intergroup
Bibliographic record
Abstract
Abstract Introduction Therapy-related CBF-AMLs represent approximately 10% of all CBF-AMLs and are associated with poorer outcomes, partly due to the associated solid tumor. Existing studies are small, and more data—especially NGS and cytogenetics—are needed to better define their characteristics and prognosis. Methods We analyzed data from a retrospective multicenter study (NCT05070208) and the prospective CBF-2006 trial (NCT00428558, Jourdan et al. 2014) from the French AML intergroup, including CBF-AML patients diagnosed between 2007–2020. Cases with prior chemo- or radiotherapy were classified as therapy-related (t-AML). Baseline characteristics were compared in the overall cohort. Outcomes were assessed in a sub-population of fit patients (≤80 years, cancer in remission, intensive chemotherapy). Centralized NGS was performed using 40- and 68-gene panels (36 genes in common), and MRD was assessed by RT-qPCR for RUNX1::RUNX1T1 and CBFB::MYH11. Results Among 749 CBF-AML patients included between 2007 and 2021, 78 had t-AML. t-AML patients were older (median age: 59 vs. 45 years, p<0.001), more likely to be female (68% vs. 44%, p<0.001), and had lower white blood cell counts (WBC) at diagnosis (median: 6 vs. 15 G/L, p<0.001). was the most common prior neoplasm (42%). Median interval from chemo/radiotherapy to t-AML onset was 38 months (IQR [interquartile range]: 25–69). Neoplasms were in complete remission after chemotherapy (74%) and/or radiotherapy (49%) at CBF-AML diagnosis in 83% pts and remained in sustained remission in 78% after a median follow up of 1.8 years. The distribution of RUNX1::RUNX1T1 and CBFB::MYH11 subtypes was similar between therapy-related and de novo cases (44% and 43% for RUNX1::RUNX1T1, p>0.9). Cytogenetically, X chromosome deletions were more frequent in t-AML (16% vs. 8%, p=0.016). t-AMLs showed fewer on NGS (63% vs. 75%, p = 0.019), and fewer FLT3 mutations (10% vs. 24%, p = 0.03). No other difference was observed in the mutational landscape of t-AML, including KIT and TP53 alterations. In the selected population of patients without active cancer at AML diagnosis and treated with intensive chemotherapy (n=693, including 57 t-AML), induction regimens were mainly based on 7+3 ( in t-AML vs 72% in non-t-AML, p=0.07) and consolidation courses on intermediate/high dose cytarabine courses (93% in t-AML vs 90% in non-t-AML, p=0.64). Gemtuzumab-ozogamycin was added to Cx in 9% of t-AML (vs. 10% of non-t-AML, p=1.0). Allogeneic transplant in first complete remission was performed in 9% of t-AML and 5% of non-t-AML (p=0.21). Therapy-related AML patients had a CR/CRp rate of 95%, not different from de novo patients (95%, p=0.74). MRD after one cycle of induction was not different in t-AML in bone marrow (median: 0.20% [IQR: 0.04-0.82%] vs. 0.17% [IQR: 0.03-0.49%], p=0.50) nor in peripheral blood (median: 0.02% [IQR: 0.002-0.14%] vs. 0.03% [IQR: 0.001-0.19%], p=0.85). With a median follow-up of 5.3 years (IQR :3.9-6.8), the 3-year cumulative incidence (CI) of relapse was 41% (95%CI [confidence interval]:27%-54%) in t-AML patients and 38% (95%CI:34%-42%) in non-t-AML patients (csHR=1.07 [95%CI:0.69-1.68], p=0.76). No difference was also observed for non-relapse mortality (NRM) (3-year CI-NRM: 2% [95%CI:0%-9%] for t-AML vs. 3% [95%CI:2%-5%] for non-t-AML, csHR=0.87 [95%CI:0.21-3.66], p=0.85). Overall survival (OS) was lower in t-AML in univariable analysis (3-year OS: 62% [95%CI:50%-77%] in t-AML vs 79% [95%CI:75%-82%] in non-t-AML, p=0.03). Nevertheless, this was not confirmed in multivariable analysis (HR=1.36, 95%CI:0.84-2.18, p=0.21 for t-AML) when accounting for age (per 10 years of age HR=1.27, 95%CI:1.14-1.42, p<0.001), WBC count (log10 scale HR=1.25, 95%CI:0.94-1.65, p=0.12), and CBF subtype (HR=1.19, 95%CI:0.87-1.62, p=0.29 for RUNX1::RUNX1T1). In patients who experienced relapse (n=249 including 21 t-AML), OS after relapse was dismal in t-AML (16% [95%CI:6%-45%] vs 56% [95%CI:50%-64%], p<0.0001). Conclusion This study shows that therapy-related CBF-AML patients are older, have lower WBC at diagnosis, and present with similar molecular profiles compared to de novo cases. Among a homogenous cohort of patients without active cancer and treated with intensive chemotherapy, there were no differences in CR/CRp rates, relapse incidence, or non-relapse mortality. Unlike previous studies, overall survival was not significantly different after multivariable adjustment for age, WBC count, and CBF subtype.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".