Advanced medullary thyroid cancer treated with Sorafenib: A case report
Bibliographic record
Abstract
Background: Medullary thyroid carcinoma (MTC) accounts for 5% of all thyroid carcinomas. As no effective systemic therapy exists, surgery is the only curative treatment for MTC. In the last few years, several clinical trials have tested the efficacy of new multi-targeted agents such as sorafenib, vandetanib, motesanib, sunitinib and pazopanib in patients with metastatic MTC. Summary: In June 2010, a 38-year-old male patient complained on pain on swallowing and coughs. Physical examination detected a hard nodule of 2 cm on the left side of his neck. A fine-needle aspiration of it yielded evidence of carcinoma. A computed tomography scan showed multiple lyphadenopathies. In August 2010, the patient underwent an incomplete thyroidectomy and received radiotherapy. In spite of that, he was still unable to swallow either solids or liquids, and suffered dyspnoea on moderate exertion. In May 2011, the patient started receiving sorafenib and levothyroxine. After 20 days, his clinical symptoms were less severe and palpable lymphadenopathies shrank by 50%. After 5 months, the patient still had no dysphagia or dyspnoea, but developed fatigue and elevated transaminases. Sorafenib was discontinued and the liver was examined by ultrasonography with no abnormal findings. After a two-week rest period, the patient resumed sorafenib from November 2011 to December 2012, achieving a clinical, biochemical and radiological response. Conclusion: This case provides limited evidence for a potential role for sunitinib in the treatment of patients with metastatic MTC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".