Coexisting Molecular Alterations Increase the Risk of Malignancy in Thyroid Nodules with Copy Number Alterations
Bibliographic record
Abstract
Molecular mutations and alterations play a role in thyroid tumorigenesis. Different alterations are associated with different clinical and pathological characteristics. Copy number alterations (CNAs) are known to be present in some thyroid tumors; however, their idiosyncratic clinicopathological implications are not yet well elucidated. A retrospective chart review was performed to identify patients with CNAs on pre-operative molecular testing results who subsequently underwent surgical treatment between January 2016 and April 2022 at McGill University teaching hospitals. Of the 316 patients with thyroid nodules who opted for molecular testing with ThyroSeqV3 followed by surgery, 67 (21.2%) nodules were positive for CNAs, including 23 Bethesda III, 31 Bethesda IV, 12 Bethesda V and 1 Bethesda VI nodules. On surgical pathology, 29.9% were benign and 70.1% were malignant or non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Among those that were malignant/NIFTP, 17.02% were considered to be aggressive cancers. The presence of other molecular alterations was found to be an independent predictor of malignancy in multivariate analysis (OR = 5.087, 95% C.I. = 1.12–23.04, p = 0.035). No unique factor was correlated with aggressiveness; however, CNA-positive thyroid nodules that were associated with high-risk mutations such as BRAF V600E, TP53, NTRK1/3 fusion, or PTEN mutation with high allele frequency (AF) ended up being aggressive cancers. Most of the CNA-positive thyroid nodules resulted in follicular patterned tumors in 41 (65.2%) cases and oncocytic tumors in 20 (29.9%) cases. This study demonstrates that 70.1% of surgically resected thyroid nodules with CNAs were malignant/NIFTP. Most CNA-positive thyroid nodules were either oncocytic patterned tumors or follicular patterned tumors. Furthermore, CNA-positive thyroid nodules were more likely to be malignant if they were associated with other molecular alterations or mutations.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".