Multiparameter Flow Cytometry-Based Residual Disease Analysis Identifies Intermediate-Risk AML Patients Who May Benefit from Allogeneic Hematopoietic Stem Cell Transplantation
Bibliographic record
Abstract
Background Allogeneic hematopoietic stem cell transplantation (alloSCT) is a curative therapeutic modality in acute myeloid leukemia (AML). While numerous studies have confirmed the benefit of alloSCT - improved overall survival (OS) and reduced cumulative incidence of relapse (CIR) - restricted mainly to the intermediate and high-risk groups, indications for alloSCT are becoming more restricted over time. Residual disease (RD) monitoring has been proven to be highly predictive of long-term AML outcomes and is now used commonly to guide ongoing therapy decisions. RD-based guidelines in AML propose the use of multiparameter flow cytometry-based RD (FRD) analyses in patients whose disease cannot be followed by molecular means (e.g. CBF AML, APL, NPM1-mutated AML). Methods We performed a retrospective review to evaluate the potential therapeutic benefit of alloSCT in AML patients who achieved first complete remission (CR1) and to further define this benefit based on the FRD status at remission. We performed a time-dependent analysis using the covariate of time-to-alloSCT as the primary endpoint of the study. The Mantel-Byar method was applied to compare time to event between the alloSCT and non-transplant groups, addressing time bias concerns that occur with alloSCT studies, according to the FRD status at the time of remission. Results The FRD assay has been part of our standard of care since 2015 with a sensitivity of 0.1%. The cohort analyzed included 435 patients treated between 2015 and 2018, of which 336 patients had FRD assessment at CR1. The patients were risk classified using the European Leukemia Network (ELN) 2017 classification which integrates cytogenetic and mutational analyses. The proportion of patients with positive FRD (RDpos) at the post-induction time-point was 35.1% (n=118). Negative residual disease (RDneg) status after induction occurred more frequently in de novo, favorable risk, and NPM1-mutated AMLs, than in the adverse risk or secondary AML groups. Overall, across all ELN 2017 groups, the impact of alloSCT was neutral for both OS and relapse free survival (RFS). A potential impact of alloSCT could be discerned, however, when patients were grouped by FRD status at CR assessment. Overall, in the RDpos group, alloSCT improved OS and RFS, while not benefitting the RDneg group. The impact of alloSCT was defined further by considering ELN 2017 risk groups, with an OS/RFS benefit observed in adverse risk patients (n=186; HR for OS 0.55 [0.31-0.99]; p=0.05); HR for RFS 0.57 [0.31-1.05], p=0.07), while an increased risk of death or of an RFS event was seen in favorable risk patients (n=151; HR for OS 4.3 [1.65-11.2], p=0.003; HR for RFS 2.29 [1.07-4.93], p=0.03). In the ELN 2017 intermediate risk patients (n=98), a survival benefit of alloSCT was not seen (HR for OS 1.05 [0.45-2.46], p=0.92; HR for RFS 0.86 [0.42-1.78], p=0.69), although alloSCT was associated with a lower CIR (HR 0.43 [0.20-0.90], p=0.03). However, when only RDpos patients were considered (n=27), trends towards benefit from alloSCT in OS (HR 0.52 [0.11-2.52], p=0.42), RFS (HR 0.38 [0.09-1.62], p=0.19), and CIR (HR 0.44 [0.07-2.72], p=0.38) were observed. In RDneg patients (n=53), alloSCT was associated only with a lower CIR (HR 0.18 [0.05-0.66], p=0.01). We then re-analyzed the data using the older UK-MRC risk classification of AML based exclusively on cytogenetics at diagnosis. This approach increased the patients in the intermediate group from 98 (ELN 2017) to 298 (UK-MRC). When using UK-MRC, an RFS benefit from alloSCT was observed for intermediate risk RDpos patients (n=211; HR 0.44 [0.20-0.96], p=0.04). Trends for benefit in OS (HR 0.45 [0.19-1.03], p=0.06) and CIR (HR 0.45 [0.20-1.04], p=0.06) were observed as well. In RDneg patients, however, an RFS/CIR benefit of alloSCT was not observed, while inferior OS was seen in the alloSCT group from increased non-relapse mortality. Conclusion Our data underscore the established benefit of alloSCT in adverse risk AML and suggest a potential benefit of this treatment modality in RDpos intermediate risk patients, thus confirming the utility of ongoing RD assessment in AML. Our results also indicate that ongoing sophistication in AML risk assignment, based on mutational profile at diagnosis, influences the potential benefit of alloSCT. Further studies are needed to better define the subgroup of RDpos intermediate risk patients who may benefit from alloSCT. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".