Remission of Ectopic Cushing Syndrome Secondary to Medullary Thyroid Cancer With Vandetanib and Selpercatinib
Bibliographic record
Abstract
) proto-oncogene. These tumors may rarely secrete adrenocorticotropin or corticotropin-releasing hormone, resulting in a paraneoplastic ectopic Cushing syndrome (ECS). Paraneoplastic ECS carries a high risk of mortality, and management is difficult due to the lack of response to antiadrenal therapies. We report on a 37-year-old man who was diagnosed with metastatic MTC and reported symptoms of cortisol excess with laboratory testing in keeping with ECS. He began treatment with vandetanib, a multitargeted tyrosine kinase inhibitor, which resulted in decreased tumor burden as well as clinical and biochemical resolution of ECS. Due to progressive structural disease 10 months later, he was switched to the selective RET inhibitor selpercatinib, which was followed by a rapid reduction of cortisol nearing the threshold of adrenal insufficiency. Tumor markers were also improved, and repeat imaging showed decreased tumor burden. Our case highlights the efficacy of tyrosine kinase inhibitors in the management of paraneoplastic ECS. Selective RET inhibitors may emerge as preferred targeted treatment options due to better efficacy and toxicity profiles compared to multitargeted inhibitors. Clinicians should monitor for adrenal insufficiency with the use of selective RET inhibitors.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".