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Record W4391283170 · doi:10.1210/jcemcr/luad174

Remission of Ectopic Cushing Syndrome Secondary to Medullary Thyroid Cancer With Vandetanib and Selpercatinib

2024· article· en· W4391283170 on OpenAlexaff
Aria Jazdarehee, Omar Abdel‐Rahman, Jennifer Jacquier

Bibliographic record

VenueJCEM Case Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVandetanibMedicineMedullary thyroid cancerInternal medicineTyrosine-kinase inhibitorThyroidCancerEndocrinologyHormoneOncologyCancer researchThyroid cancerTyrosine kinaseReceptor

Abstract

fetched live from OpenAlex

) 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.289
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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