Diagnostic Significance of CD20 and FMC7 Expression in B-Cell Disorders
Bibliographic record
Abstract
We analyzed by flow cytometry the expression of CD20 and FMC7 in cell suspensions from 932 patients, including 630 cases of chronic lymphocytic leukemia (CLL), 23 cases of other B-cell leukemias, and 279 cases of B-cell non-Hodgkin lymphoma (B-cell NHL). CD20 was positive in 94.5% of cases; FMC7 was positive in 35.7%. There was a correlation between CD20 and FMC7 expression in patients with B-cell NHL (P < .001) but not CLL (P = .1). We also tested a scoring system in which FMC7 was replaced by CD20 and compared it with our current scoring system for CLL. With this modification, the accuracy of the scoring system for differentiating CLL from other non-CLL disorders fell from 94.4% to 81.5%. In CD20+ CLL, the intensity of CD20 expression correlated with FMC7 and low scores (P < .001 for both comparisons). We suggest that the particular conformation of CD20 recognized by FMC7 is manifested only in cells with strong CD20 expression, which is not the case for CLL. FMC7 is of greater diagnostic value than CD20 for distinguishing CLL from other B-cell disorders; we recommend its continued use for this purpose.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".