Flow cytometry immunophenotyping in integrated diagnostics of patients with newly diagnosed cytopenia: one tube 10‐color 14‐antibody screening panel and 3‐tube extensive panel for detection of<scp>MDS</scp>‐related features
Bibliographic record
Abstract
Acute leukemia, myelodysplastic syndromes (MDS), myeloproliferative neoplasms and lymphomas are the most prevalent diagnoses in adults presenting with new onset cytopenia. Here, we describe two 10-color panels of surface markers (screening and comprehensive panel) applied at the Flow Cytometry Laboratory, University Health Network, Toronto, ON, Canada. A 10-color flow cytometry is applied using the stain-lyse-wash sample preparation method. In patients with <10% blasts and no clear involvement by hematological malignancy based on cytomorphological evaluation of bone marrow (BM) smear, the recently published one-tube 10-color 14-antibody screening panel is applied. This panel allows detection of major B- and T-cell abnormalities, enumeration of cells in blast region (CD45 dim), and gives insight into myeloid BM compartment, including calculation of four-parameter score for MDS-related abnormalities. In patients who present with ≥10 - <20% blasts in blood or BM smears, a comprehensive three-tube panel of surface markers is used up front. The analysis is focused on the detection of abnormal antigen expression patterns not seen in normal/reactive BM, according to the guidelines developed by International/European LeukemiaNet Working Group for Flow Cytometry in MDS. In patients with ≥20% blasts, an additional tube is added to allow the detection of cytoplasmic markers necessary to diagnose mixed phenotype acute leukemia.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".