Calcitonin negative Medullary Thyroid Carcinoma: a challenging diagnosis or a medical dilemma?
Bibliographic record
Abstract
BACKGROUND: Medullary thyroid carcinoma is a neuroendocrine tumor belonging form a malignant growth of the thyroid parafollicular C-cells, representing from 1 to 10% of all thyroid cancer. The biochemical activity of medullary thyroid carcinoma includes the production of calcitonin and carcinoembryogenic antigen, which are sensitive tumor markers, facilitating the diagnosis, follow-up and prognostication. The diagnosis is reached through the identification of high basal calcitonin serum level or after pentagastrin stimulation test. Medullary thyroid carcinoma is able to produce other relevant biomarkers as procalcitonin, carcinoembryionic antigen and chromogranin A. In Literature are described few cases of medullary thyroid carcinoma without elevation of serum calcitonin, an extremely rare event. The aim of this study was to analyse the presentation, the main features and therapeutic management of medullary thyroid carcinoma associated with negative serum calcitonin levels. METHODS: Using the PubMed database, a systematic review of the current Literature was carried out, up to February 2018. Finally, nineteen articles met our inclusion criteria and were selected according to the modified Newcastle-Ottawa scale. RESULTS: Fourty-nine patients with definitive pathology confirming medullary thyroid carcinoma and with calcitonin serum level in the normal range were identified (24 female, 24 male and not reported gender in 1 case). Mean age was 51.7 years. Serum calcitonin levels were reported for 20 patients with a mean value of 8.66 pg/mL and a range of 0.8-38 pg/mL. Despite the low or undetectable calcitonin serum level, at immunochemistry in almost the half of the cases reported by the Authors, the tumors presented diffuse or focal positivity for calcitonin and carcinoembryionic antigen, while was reported a chromogranin A positivity in 41 of the 43 tested patients. CONCLUSIONS: Calcitonin negative medullary thyroid carcinoma is an extremely rare pathology. The diagnosis and the surveillance is often challenging and delayed, due to the lack of elevation of serum markers as calcitonin and carcinoembryionic antigen. Further studies are needed, to better define options for management of non secretory medullary thyroid carcinoma and to identify new and reliable biomarkers associated to diagnosis and relapse of this medical dilemma.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".