Improved identification of clinically relevant <scp>Acute Leukemia</scp> subtypes using standardized <scp>EuroFlow</scp> panels versus non‐standardized approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rare acute leukemia (AL) components or subtypes such as blastic plasmacytoid dendritic cell neoplasm (BPDCN) or early T-cell precursor acute Lymphoblastic Leukemia (ETP-ALL) can be difficult to detect by routine flow cytometry due to their immunophenotypes overlapping with other poorly differentiated AL. We hypothesized that using standardized EuroFlow™ Consortium approach could better diagnose such entities among cases that previously classified as acute myeloid leukemia (AML)-M0, AML with minimal differentiation, AML with myelodysplasia-related changes without further lineage differentiation, and AL of ambiguous lineage. In order to confirm this hypothesis and assess whether these AL subtypes such as BPDCN and ETP-ALL had previously gone undetected, we reanalyzed 49 banked cryopreserved sample cases using standardized EuroFlow™ Consortium panels. We also performed target sequencing to capture the mutational commonalities between these AL subtypes. Reanalysis led to revised or refined diagnoses for 23 cases (47%). Of these, five diagnoses were modified, uncovering 3 ETP-ALL and 2 typical BPDCN cases. In 12 AML cases, a variable proportion of immature plasmacytoid dendritic cell and/or monocytic component was newly identified. In one AML case, we have identified a megakaryoblastic differentiation. Finally, in five acute lymphoblastic leukemia (ALL) cases, we were able to more precisely determine the maturation stage. The application of standardized EuroFlow flow cytometry immunophenotyping improves the diagnostic accuracy of ALs and could impact treatment decisions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it