Bibliographic record
Abstract
Parathyroid carcinoma is a rare type of endocrine cancer, with significant morbidity and mortality associated with parathyroid hormone (PTH)-mediated hypercalcemia. Concerning clinical features for parathyroid cancer include severe hypercalcemia (albumin-corrected calcium > 3 mmol/L), a palpable neck mass ( > 3 cm), 3rd/2nd generation PTH assay ratio ( > 1), and intraoperative suspicion of local invasion or regional metastasis. A definite diagnosis of malignancy is rendered when a parathyroid tumor presents one of the following clinicopathological features: (1) vascular invasion, (2) perineural invasion, (3) gross invasion into adjacent anatomical structures, and/or (4) metastasis. In difficult cases, the use of ancillary biomarkers is critical to establish an accurate diagnosis. Recent advances in molecular pathology have uncovered the important role of CDC73/HRPT2, a tumor suppressor gene deregulated in parathyroid carcinomas. Loss of nuclear and/or nucleolar expression of parafibromin (the gene product of CDC73/HRPT2) is now regarded as a diagnostic, prognostic and predictive biomarker for parathyroid carcinoma. Furthermore, over 15-20% of seemingly sporadic parathyroid carcinomas have underlying germline CDC73/HRPT2 mutations. As a result, many centers have integrated the use of ancillary biomarkers, notably parafibromin staining, in their routine practise. Radical surgery with en bloc resection has emerged as a primary treatment modality in parathyroid cancer, achieving cure in some patients. However, in those with inoperable disease, there remains a dire need for new therapies, as current treatments are largely ineffective. This review provides an update on the current knowledge of parathyroid carcinoma and highlights its exciting changes in endocrine practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".