Hürthle Cell Tumors
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Since ret/PTC gene rearrangements are specific to papillary thyroid carcinoma (PTC), the diagnosis of Hürthle cell PTC (HCPTC) has recently been expanded to include a subset of Hürthle cell tumors (HCTs) that may lack both papillary architecture and/or classic nuclear features but that harbor a ret/PTC gene rearrangement. We hypothesize that such HCPTCs behave in a fashion analogous to other papillary carcinomas, while Hürthle cell carcinomas (HCCs) behave similarly to follicular carcinomas. EDUCATIONAL OBJECTIVES: At the conclusion of this article, participants should be able to discuss HCTs and to identify HCPTCS using molecular techniques. METHODS: A retrospective chart review was carried out on 56 patients with HCTs. All pathological specimens were analyzed for ret/PTC gene rearrangements. Hürthle cell adenoma (HCA) was defined as an HCT that did not exhibit capsular and/or vascular invasion and that lacked a ret/PTC gene rearrangement when evaluated by immunohistochemical and reverse transcription polymerase chain reaction analysis. An HCC was defined as an HCT with capsular and/or vascular invasion that lacked a ret/PTC gene rearrangement, and an HCPTC was defined as any HCT that harbored a ret/PTC gene rearrangement. RESULTS: The subclassification of the 56 HCTs was as follows: 21 HCAs, 15 HCCs, and 20 HCPTCs. No patients with HCA or HCC were ret/PTC positive. Five of the 6 patients with definite lymph node metastasis were in the HCPTC group, demonstrating that molecular analysis helps to explain biological behavior. CONCLUSIONS: Hürthle cell neoplasms can now be classified using histopathological as well as molecular criteria. It appears that the new subclassification of malignant HCTs into follicular (HCC) and papillary (HCPTC) variants identifies 2 distinct biological groups.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it