Targeted use of fluorescence in situ hybridization (FISH) in cytospin preparations
Bibliographic record
Abstract
BACKGROUND: Fluorescence in situ hybridization (FISH) results from fine needle aspirates (FNA) of B-cell non-Hodgkin lymphomas (NHLs) were reviewed to 1) investigate the value added by using specific gene rearrangement probes to lymphoma diagnosis, prognosis, and subtyping; and 2) evaluate the prevalence of cytogenetic alterations other than specific translocations. METHODS: FISH results from assays performed on cytospin preparations from NHL FNAs over a 6-year period (2003-2009) were selected. Immunophenotyping, clinical data, and cytomorphologic data were reviewed according to the current World Health Organization (WHO) classification system. Hybridized probes, the purpose for the assay (subtyping or prognosis), and the cytogenetic abnormalities observed were retrieved from cytology reports. Data was categorized according to specific rearrangements and other chromosomal abnormalities. RESULTS: Successful results were obtained in 284 (95.3%) of 298 cases from 282 patients. Abnormalities were found in 216 (76%) cases and 68 (24%) did not show alteration. Among cases submitted for subtyping, 198 showed FISH-positive results, and specific gene rearrangements were found in 122 (61.6%) cases as follows: follicular 82, mantle cell 21, marginal zone 3, "dual hit" 13, and Burkitt lymphoma 3. In 21 cases, abnormalities were useful for prognosis. Nonspecific alterations alone or in combination with translocations were found in 98 cases. CONCLUSIONS: FISH performed on cytospin preparations was useful for confirmation of specific subclasses of NHL and may also provide valuable prognostic information. Cytogenetic abnormalities other than specific translocations were frequently found and could provide supportive evidence for a definitive diagnosis of lymphoma in FNA.
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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 | 0.001 |
| 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) | 0.002 | 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".