Inherited Follicular Epithelial-Derived Thyroid Carcinomas: From Molecular Biology to Histological Correlates
Bibliographic record
Abstract
Cancer derived from thyroid follicular epithelial cells is common; it represents the most common endocrine malignancy. The molecular features of sporadic tumors have been clarified in the past decade. However the incidence of familial disease has not been emphasized and is often overlooked in routine practice. A careful clinical documentation of family history or familial syndromes that can be associated with thyroid disease can help identify germline susceptibility-driven thyroid neoplasia. In this review, we summarize a large body of information about both syndromic and non-syndromic familial thyroid carcinomas. A significant number of patients with inherited non-medullary thyroid carcinomas manifest disease that appears to be sporadic disease even in some syndromic cases. The cytomorphology of the tumor(s), molecular immunohistochemistry, the findings in the non-tumorous thyroid parenchyma and other associated lesions may provide insight into the underlying syndromic disorder. However, the increasing evidence of familial predisposition to non-syndromic thyroid cancers is raising questions about the importance of genetics and epigenetics. What appears to be "sporadic" is becoming less often truly so and more often an opportunity to identify and understand novel genetic variants that underlie tumorigenesis. Pathologists must be aware of the unusual morphologic features that should prompt germline screening. Therefore, recognition of harbingers of specific germline susceptibility syndromes can assist in providing information to facilitate early detection to prevent aggressive disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".