A 10-color flow cytometry panel for diagnosis and minimal residual disease in chronic lymphocytic leukemia
Bibliographic record
Abstract
Diagnosis and minimal residual disease (MRD) monitoring of chronic lymphocytic leukemia (CLL) by flow cytometry currently requires multiple antibody panels. We added CD23 and CD200 to the EuroFlowTM lymphoid screening tube (LST) to create a 10-color modified LST (mLST) capable of diagnosing typical CLL in a single tube. We then explored if the mLST could be used for MRD by comparing its performance to the European Research Initiative on CLL (ERIC) panel using spiked cryopreserved and fresh patient samples. Over 1 year of use in our clinical laboratory, the mLST diagnosed CLL without further immunophenotyping in 56% of samples with an abnormal clone. There was good agreement in MRD results between the mLST and ERIC panels. Therefore, the mLST can streamline CLL diagnosis by reducing technician time and the number of panels required. It may have the potential to screen for MRD in laboratories without access to dedicated panels (ERIC).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".