Role of vandetanib in the management of medullary thyroid cancer
Bibliographic record
Abstract
Role of vandetanib in the management of medullary thyroid cancer Maryse Brassard1*, Geneviève Rondeau2* 1Endocrinology Service, Department of Medicine, Centre Hospitalier Universitaire Affilié (CHA), Laval University, Quebec, Canada; 2Endocrinology Service, Department of Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), University of Montreal, Montreal, Canada*Both authors contributed equally to this articleAbstract: Traditionally available treatments, like cytotoxic chemotherapy and external-beam radiation therapy, are limited and essentially ineffective for metastatic medullary thyroid carcinoma (MTC). In the last decade, small-molecule tyrosine kinase inhibitors (TKI) have been introduced in the field of thyroid cancer, after having been shown effective in a wide variety of other tumors. This review focuses on vandetanib (ZD6474, ZactimaTM; AstraZeneca) and its role in the treatment of MTC. Vandetanib is an oral TKI that targets VEGF receptors 2 and 3, RET, and at higher concentrations, the epidermal growth factor (EGF) receptor. This drug has been tested in two important phase II studies which demonstrated that both the 100 and 300 mg/day dosage of vandetanib have antitumor activity on advanced MTC. A phase III trial (ZETA trial) evaluating vandetanib in 331 patients with locally advanced or metastatic MTC showed a significant prolongation of PFS for patients receiving vandetanib compared with placebo. Toxicity surveillance in all studies reported high rates of adverse effects with diarrhea, rash, fatigue and nausea being the most commonly experienced by patients. Vandetanib is currently approved in the United States for unresectable locally advanced or metastatic MTC and has become a new standard of care in this rare and indolent pathology.Keywords: vandetanib, medullary thyroid cancer, RET mutation, VEFGR
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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) | 0.000 | 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".