Bone marrow staging of patients with non-Hodgkin lymphoma by flow cytometry
Bibliographic record
Abstract
BACKGROUND: Immunophenotypic analysis is an established tool in the diagnosis and classification of many hematolymphoid disorders; however, the role of flow cytometry (FC) in detecting bone marrow involvement during the staging of non-Hodgkin lymphoma (NHL) has yet to be defined. METHODS: The authors retrospectively analyzed 157 staging and 70 restaging bone marrow biopsies on which morphologic and FC analyses were performed; these biopsies were taken from 195 consecutive patients. Bone marrow biopsies were blindly and independently reviewed and determined to be positive, negative, or suspicious for morphologic involvement by NHL, with disagreements settled by a third reviewer. A selected panel of monoclonal antibodies was used to determine whether bone marrow involvement was immunophenotypically positive (>5%), minimal (<5%), negative, or nondiagnostic. RESULTS: FC and morphology agreed in 78% of cases (178 of 227: 129 both negative, 49 both positive) and were discrepant in 22% (49 of 227). Seven percent (16 of 227) were morphologically positive but showed no evidence of disease on FC, whereas 12% (27 of 227) were positive by FC but had no morphologic involvement. Of the 162 morphologically negative or suspicious bone marrows, 27 were shown to be involved by FC, resulting in a false-negative detection rate of 17%. Most of these (22 of 27, 81%) had minimal detectable disease. Seven percent of Stage I and 26% of Stage II NHL cases with negative staging bone marrow morphologically were found to be involved by FC. CONCLUSIONS: Neither morphologic examination of bone marrow biopsy specimens nor FC alone is adequate to detect all cases of NHL with bone marrow involvement. FC is most sensitive for detecting minimal bone marrow lymphoma, whereas morphology will detect most cases in which involvement is >5%. Cases of early stage NHL with morphologically negative bone marrow could potentially be restaged as Stage IV on the basis of FC results. The clinical importance of minimal bone marrow involvement by NHL needs further evaluation.
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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 | 0.006 |
| 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) | 0.001 | 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".