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Record W4415359371 · doi:10.3390/cancers17203376

Molecular Testing and Surgical Outcomes in Bethesda III and IV Thyroid Nodules: A Retrospective Cohort Study

2025· article· en· W4415359371 on OpenAlexaffabout
Alexandra E. Payne, Layla Gobeil, Marc Pusztaszeri, Isabelle Bannister, Saruchi Bandargal, Sabrina Daniela da Silva, Véronique‐Isabelle Forest

Bibliographic record

VenueCancers · 2025
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsJewish General HospitalQueen's UniversityMcGill University
Fundersnot available
KeywordsThyroid nodulesIndeterminateRetrospective cohort studyThyroidectomyThyroidConcordanceThyroid cancerCohort

Abstract

fetched live from OpenAlex

Background: Bethesda III and IV thyroid nodules, which fall under the category of indeterminate cytology, pose challenges in clinical decision-making due to their ambiguous risk of malignancy. Molecular testing has been increasingly employed to aid risk stratification and optimize the extent of surgical intervention. Methods: A retrospective review of 410 patients with Bethesda III and IV thyroid nodules who underwent thyroid surgery at McGill University teaching hospitals between January 2016 and April 2022. Patients were grouped based on whether or not they underwent preoperative molecular testing. Data were collected on demographic variables, histopathologic diagnosis, mutation profiles, and surgical outcomes. The primary outcome was to assess for concordance between surgical intervention and final pathology in both groups, with a focus on identifying optimal versus suboptimal management. Optimal management is defined as surgery appropriate to the aggressiveness of disease, meaning a hemi-thyroidectomy for a non-aggressive malignancy, total thyroidectomy for an aggressive malignancy, and no surgery for a benign nodule. Furthermore, suboptimal management includes unnecessary surgery or incorrect surgery for the level of aggressivity of the nodule. Results: Among the 410 patients, 203 underwent molecular testing, while 207 did not. Of those who underwent molecular testing, 117 had Bethesda III nodules and 86 had Bethesda IV nodules. In the non-tested group, 129 and 78 patients had Bethesda III and IV nodules, respectively. Optimal surgical intervention was achieved in 67.5% of patients who underwent molecular testing, compared with 25.1% in those who did not (p < 0.001). Subgroup analysis revealed that 61.5% of Bethesda III nodules with molecular testing received optimal care versus 21.0% of those without testing. In the Bethesda IV cohort, optimal surgery was achieved in 75.6% with testing versus 32.1% without. Among the suboptimally managed patients, 70.1% (155/221) were from the group that did not undergo molecular testing. In addition, molecular testing identified aggressive mutations such as BRAF V600E and TERT promoter mutations more frequently in Bethesda III nodules, while RAS-like mutations, associated with indolent behavior, predominated in Bethesda IV nodules. Conclusions: In this study, molecular testing significantly improved risk stratification and the likelihood of optimal surgical management in patients with Bethesda III and IV thyroid nodules. Incorporating molecular diagnostics into the standard preoperative workflow may enhance patient care, reduce unnecessary surgeries, and optimize the extent of surgery. Future studies should evaluate the cost-effectiveness and broader implementation of molecular testing in diverse healthcare settings.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.290
Teacher spread0.279 · 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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Citations2
Published2025
Admission routes2
Has abstractyes

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