The role of fine-needle aspiration in the diagnosis of thyroid lymphoma: a retrospective study of nine cases and review of published series
Bibliographic record
Abstract
AIMS: To review the clinicopathological, cytomorphological and immunophenotyping data from new cases and published series of thyroid lymphoma diagnosed by fine-needle aspiration (FNA), in order to identify useful diagnostic features. METHODS: Cases from 1988 to 2009 with an FNA diagnosis of thyroid lymphoma were selected from hospital records. An electronic MEDLINE and EMBASE search retrieved published series from 1980 to 2009. Available clinical, cytomorphological and immunophenotyping data from all cases were collected. In our cases, cytology slides and available surgical specimens were also reviewed. RESULTS: There were nine cases from eight of our patients, and 70 reviewed cases from eight series with at least four patients each. The most common presentation was a rapidly enlarging thyroid mass. Average patient age was 61 years in reviewed cases and 72 years in our cases. Large-cell lymphoma was the predominant subtype, revealing relatively monotonous populations of large, abnormal lymphoid cells. One of our cases, later diagnosed as marginal zone lymphoma, showed small lymphocytes with plasmacytoid features. Immunoprofiling information was available in five of our cases (three by immunocytochemistry and two by laser scanning cytometry) and in 34 reviewed cases (22 by immunocytochemistry, six by flow cytometry, and six by flow cytometry or immunocytochemistry). CONCLUSIONS: Cytological diagnosis of thyroid lymphoma requires careful analysis of morphological, clinical and immunophenotypic information. The presented data suggest certain helpful features: a fast-growing nodule in an elderly patient, a monotonous population of large abnormal cells in a background of lymphoglandular bodies, a predominant population of plasmacytoid lymphocytes, and immunophenotyping demonstrating light chain restriction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".