Characteristics of Lymphoproliferative Disorders with More Than One Aberrant Cell Population as Detected by 10‐Color Flow Cytometry
Bibliographic record
Abstract
BACKGROUND: We have evaluated the frequency of lymphoproliferative disorders with more than one aberrant population of monotypic B-cells detected during routine hematopathological diagnostics. MATERIALS AND METHODS: 2600 samples peripheral (blood, bone marrow, fine-needle aspirate, lymph node, and pleural fluid cell suspensions) were analyzed using a 10-color B-cell panel and a 10-color T-cell panel. A 10-color plasma cell/lymphoplasmacytic panel was performed when appropriate. RESULTS: 790/2600 samples (30%) showed at least one aberrant B-cell population and 27(1%) showed an aberrant T-cell population. 41/790 samples (5.1%) showed two aberrant B-cell populations. Thirteen patients had two B-cell populations with different surface immunoglobulin restriction (one kappa+ and one lambda+), most with B-cell chronic lymphocytic leukemia-related phenotype. Five cases showed two B-cell populations with the same light chain restriction but distinctly different immunophenotypes. In 23 cases, two populations had the same light chain restriction and differed by expression of one or 2 markers, thus, a possibility of intraclonal differentiation could not be excluded. Cases with possible intraclonal differentiation had a significantly higher proportion of aberrant B-cells than those with two coexisting aberrant B-cell populations (49.9% vs. 27.7%, p = 0.008). In only one sample one population of clonal B-cell and one clonal T-cell population with large granular lymphocyte related phenotype were found. CONCLUSION: Using our panels 5.1% of cases with lymphoproliferative disorder-associated aberrant findings show two aberrant (clonal) lymphoid and/or plasma cell populations. © 2016 International Clinical Cytometry Society.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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 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".