Characteristics of PTEN Mutation in Thyroid Tumours: A Retrospective Chart Review
Bibliographic record
Abstract
While some studies suggest that PTEN mutations correlate with a low-risk phenotype in pediatric thyroid nodules, the relationship between the mutation and malignancy in the adult populations is abstruse. This study investigated whether PTEN mutations result in thyroid malignancy, and whether these malignancies are aggressive. This multicenter study involved 316 patients who underwent preoperative molecular testing, and subsequent lobectomy or total thyroidectomy at two quaternary care hospitals. A four-year retrospective review was performed on the 16 charts of patients that opted for surgery following a positive PTEN mutation on molecular testing results from January 2018 to December 2021. Of the total 16 patients, 37.5% (n = 6) had malignant tumours, 18.75% (n = 3) had non-invasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTPs), and 43.75% (n = 7) had benign disease. Aggressive features were detected in 33.33% of the malignant tumours. Malignant tumours were found to have a statistically significant higher allele frequency (AF). The aggressive nodules were all poorly differentiated thyroid carcinomas (PDTCs) with copy number alterations (CNAs) and the highest AFs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".