The Evolving Treatment Landscape of Medullary Thyroid Cancer
Bibliographic record
Abstract
OPINION STATEMENT: Genetic assessment is crucial to address the correct treatment for advanced medullary thyroid cancer (MTC). Multi tyrosine kinase inhibitors (mTKIs) cabozantinib and vandetanib are good first line options, even vandetanib prescription is currently limited to RET mutated patients. Selective RET inhibitors such as pralsetinib could be a preferred upfront treatment in case of RET mutated MTC presenting common or gatekeeper RET mutations (e.g. M918T; V804L/M). Selpercatinib, otherwise, can be prescribed as the second line after disease progression to mTKIs. The best option for subsequent lines is to consider inclusion in clinical trials or alternatively other mTKIs such as sunitinib, sorafenib, lenvatinib, or pazopanib could be evaluated. New perspectives include next-generation RET inhibitors able to overcome resistance mechanisms responsible for disease progression to standard mTKIs and RET inhibitors, and immunotherapy for MTC presenting with high tumor mutational burden.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".