Screening bone marrow samples for abnormal lymphoid populations and myelodysplasia‐related features with one 10‐color 14‐antibody screening tube
Bibliographic record
Abstract
BACKGROUND: We have designed one-tube 14-antibody 10-color flow cytometry (FCM) panel that would provide maximum information on lymphoid and myeloid cell subsets in bone marrow aspirates (BMA) from patients with cytopenia(s). SAMPLES AND METHODS: BMA from 8 normal donors, from 286 non-malignant hospital controls, 92 myelodysplastic syndromes (MDS), 47 myeloproliferative neoplasms (MPN), and from 14 MDS/MPN patients were investigated. One tube 14-monoclonal antibody (MAb) 10-fluorochrome panel included: kappa+CD4 FITC, Lambda+CD8 PE, CD3 + CD14 ECD, CD34 APC, CD20+CD56 PC7, CD10 APC-A750, CD19 APC-A700, CD33 PC5.5, CD5 PB, and CD45 KO. Kappa/lambda expression was evaluated separately in CD19+, CD10+ and CD5+ B-cells. CD4+CD3+, CD8+CD3+, CD5+CD3+ T-lymphocyte subsets were enumerated. Blasts were evaluated using CD45/SSC and CD34 gating. The FCM score for MDS (sc. Ogata score) included CD34+ myeloblast and B-progenitor cluster size, myeloblast/lymphocyte CD45 expression, and granulocyte/lymphocyte SSC ratio. RESULTS: Abnormal lymphoid populations or increased plasma cells were found in 18 patients (4%). A 43/92 BMA from MDS and 7/14 from MDS/MPN patients had score >2. Score >2 had 92.5% positive predictive value for MDS/MDS-MPN diagnosis. Negative predictive value for MDS/MDS-MPN was 83% for scores under 3 and 88% for scores under 2. All but two of normal/hospital control samples had FCM score <3 (99%). Differences in scores between MDS & MDS/MPN and the control groups were statistically significant (P < 0.0001). CONCLUSIONS: Our one-tube FCM panel can be easily applied to screening for aberrant lymphoid populations and myelodysplasia-related features. MDS scores >2 are highly indicative of MDS or MDS-MPN.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".