Fusion transcript analysis reveals slower response kinetics than multiparameter flow cytometry in childhood acute myeloid leukaemia
Bibliographic record
Abstract
INTRODUCTION: Analysis of measurable residual disease (MRD) is increasingly being implemented in the clinical care of children and adults with acute myeloid leukaemia (AML). However, MRD methodologies differ and discordances in results lead to difficulties in interpretation and clinical decision-making. The aim of this study was to compare results from reverse transcription quantitative polymerase chain reaction (RT-qPCR) and multiparameter flow cytometry (MFC) in childhood AML and describe the kinetics of residual leukaemic burden during induction treatment. METHODS: In 15 children who were treated in the NOPHO-AML 2004 trial and had fusion transcripts quantified by RT-qPCR, we compared MFC with RT-qPCR for analysis of MRD during (day 15) and after induction therapy. Eight children had RUNX1::RUNX1T1, one CBFB::MYH11 and six KMT2A::MLLT3. RESULTS: When ≥0.1% was used as cut-off for positivity, 10 of 22 samples were discordant. The majority (9/10) were MRD positive with RT-qPCR but MRD negative with MFC, and several such cases showed the presence of mature myeloid cells. Fusion transcript expression was verified in mature cells as well as in CD34 expressing cells sorted from diagnostic samples. CONCLUSIONS: Measurement with RT-qPCR suggests slower response kinetics than indicated from MFC, presumably due to the presence of mature cells expressing fusion transcript. The prognostic impact of early measurements with RT-qPCR remains to be determined.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".