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Record W4417272707 · doi:10.3390/curroncol32120700

Mitotane-Induced Hypothyroidism and Dyslipidemia in Adrenocortical Carcinoma: Sex Differences and Novel Evidence from a Thyroid Cell Model

2025· article· en· W4417272707 on OpenAlexvenueno aff
Irene Tizianel, A. Beber, Alberto Madinelli, Mario Caccese, Susi Barollo, Loris Bertazza, Elena Ruggiero, Simona Censi, Caterina Mian, Filippo Ceccato

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsnot available
FundersIstituto Oncologico Veneto
KeywordsMitotaneDyslipidemiaThyroidThyroid functionPropylthiouracilThyroid cancerToxicityCentral hypothyroidism

Abstract

fetched live from OpenAlex

Adrenocortical carcinoma (ACC) is a rare and aggressive cancer with limited treatment options, commonly managed with mitotane, which can cause serious side effects, including central hypothyroidism and dyslipidemia. This study aimed to evaluate the incidence, clinical features, and relationship between mitotane-induced central hypothyroidism and dyslipidemia in ACC patients, as well as to investigate mitotane's direct toxic effects on thyroid cells. Thirty-eight ACC patients treated with mitotane for at least six months were monitored for thyroid function and lipid profiles. Central hypothyroidism developed in 50% of patients with normal baseline thyroid function, mostly women, who were at higher risk. Dyslipidemia occurred in 40% of patients, more frequently in men, and appeared earlier than hypothyroidism. In vitro experiments on rat thyroid cells demonstrated a dose-dependent toxic effect of mitotane on cell viability. No significant link was found between hypothyroidism and dyslipidemia risk. These findings reveal sex-specific susceptibilities to mitotane toxicity and provide novel evidence of direct mitotane-induced thyroid cell damage. This insight supports the need for careful thyroid and lipid profile monitoring during mitotane treatment and may inform the development of safer therapies for ACC.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.125
GPT teacher head0.379
Teacher spread0.254 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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