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Clinical and molecular features and survival in thyroid cancer with brain metastases.

2024· article· en· W4399318770 on OpenAlexaff
Carly C. Barron, Thais Baccili Cury Megid, Yangqing Deng, Erick Figueiredo Saldanha, Gordon Taylor Moffat, Richard Thomas O'Dwyer, Aruz Mesci, Jelena Lukovic, Richard Tsang, Özgür Mete, Monika K. Krzyzanowska, Lucy Xiaolu

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMedicineThyroid cancerOncologyBrain metastasisBrain cancerCancerThyroidInternal medicinePathologyCancer researchMetastasis

Abstract

fetched live from OpenAlex

2023 Background: Brain metastases (BM) in advanced thyroid cancer are rare; however, they may be underreported as staging brain imaging is not routine. Prognostic features and molecular alterations for this group are poorly described. We characterized the clinical and molecular features of thyroid cancer with BM and evaluated differences in survival. Methods: In this single-center retrospective analysis, patients with metastatic radioactive iodine refractory well-differentiated, poorly-differentiated, or medullary thyroid carcinoma seen at the Princess Margaret Cancer Center from 2007-2022 were included. Electronic medical records were reviewed to collect clinicopathologic and treatment data. All patients had tumor next-generation sequencing (NGS) by a targeted gene panel. Overall survival (OS) from initial medical oncology consultation was analyzed using the Kaplan-Meier method and univariate and multivariate Cox proportional hazards models. Results: Of 248 patients with advanced thyroid cancer, 41(17%) were diagnosed with BM. The median interval from thyroid cancer diagnosis to BM development was 6.49 years (y) (IQR 3.51- 14.35 y). The median age at the time of BM diagnosis was 63.6 y and 23 (56%) were male. Most (76%) were asymptomatic at the diagnosis of BM and 80% had an ECOG of 0-1. Among patients with well-differentiated histology, 27 (18%) developed BM, while 7 (12%) with poorly-differentiated and 7 (19%) with medullary thyroid cancer developed BM. The most common molecular alterations included BRAFV600E (n=19), TERT (n=11), RAS (n=9), RET (n=8), and FANCA (n=3). Patients were treated with surgery (n=5), stereotactic radiation (n=21), whole brain radiation therapy (n=12), or a combination of both (n=2). OS was similar in patients with BM compared to those without (6.05 vs 6.45 y). There were no differences in histology or molecular alterations between patients that developed BM compared to those who did not. The median survival from the time of BM was 3.23 y. Patients with BM with ≥4 lesions had worse survival (0.52 vs 5.09 y, p=0.01). There were no differences in survival based on histology, symptoms, treatment or molecular alterations among those with BM. Conclusions: This is one of the largest reported thyroid BM cohorts and the first with complete NGS. The prevalence of BM in our cohort was higher than previously described, often diagnosed incidentally. Screening for BM in advanced thyroid cancer may detect higher rates, offering prognostic insights. While the number of BM was predictive of survival, molecular alterations did not predict BM development or survival and larger studies are needed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.475
Teacher spread0.411 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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