Diagnosis and management of parathyroid carcinoma: a state-of-the-art review
Bibliographic record
Abstract
Parathyroid carcinoma is one of the least common endocrine malignancies and accounts for approximately 1% of all patients with primary hyperparathyroidism. A systematic review of peer-reviewed literature published between January 2000 and March 2022 via Medline, Embase, Cochrane Central Register of Controlled Trials, EudraCT, ClinicalTrials.gov, CINAHL and SCOPUS was conducted. Manuscripts were eligible if they included data on adult non-pregnant populations with parathyroid carcinoma. No restrictions regarding interventions, comparators or duration of follow-up were imposed. Single case reports, reviews or meta-analyses were excluded. Outcomes of interest were molecular pathogenesis, clinical presentation, differential diagnosis, treatment, follow-up and overall survival. Study quality was evaluated using the Newcastle-Ottawa Scale for observational studies. This review included 75 studies from 17 countries, reporting on more than 3000 patients with parathyroid carcinoma. CDC73 mutation has been recognised as playing a pivotal role in molecular pathogenesis. Parathyroid carcinoma typically presents with markedly increased calcium and parathyroid hormone levels. The most frequently described symptoms were bone and muscle pain or weakness. En bloc resection remains the gold standard for the surgical approach. The 5-year overall survival ranged from 60 to 93%, with resistant hypercalcaemia a significant cause of mortality. Emerging evidence indicating that targeted therapy, based on molecular biomarkers, presents a novel treatment option. The rarity of PC and need for personalised treatment warrant multidisciplinary management in a 'centre of excellence' with a track record in PC management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".