Mutational status may supersede tumor size in predicting the presence of aggressive pathologic features in well differentiated thyroid cancer
Bibliographic record
Abstract
Background In clinical practice, thyroid tumor size plays a critical role in the staging of thyroid malignancies and in the selection of nodules that should undergo ultrasound-guided fine-needle aspiration. Thyroid tumor size is influenced by the elapsed time since the beginning of oncogenesis and by the presence of somatic mutations driving growth, such as BRAF V600E mutations, associated with aggressive phenotypes, and RAS-like mutations, associated with more indolent behavior. Although large nodules are often considered to be more alarming, the true impact of tumor size on prognosis remains controversial. The aim of this study was to assess the relationship between mutational status, tumor size and aggressiveness, with emphasis on BRAF V600E and RAS-like mutations. Method We conducted a multicentric retrospective chart review in Montréal, Canada, of all patients who underwent thyroid surgery between January 2016 and December 2020, with well-differentiated thyroid cancer on final pathology, and who had undergone molecular testing revealing the presence of BRAF V600E mutations or RAS-like mutations ( NRAS, HRAS or KRAS). Results We included 214 cases. There were 117 (54.7%) cases of BRAF V600E and 97 (45.3%) cases of RAS-like mutations. The BRAF V600E group was statistically associated with a smaller mean tumor size when compared with the RAS group of 1.55 cm and 2.04 cm, respectively. In a multivariate model, tumors with BRAF V600E mutations were also more likely to display aggressive pathological features, including extra-thyroidal extension, lymph node metastasis, columnar cell features, tall cell histology, or hobnail histology (OR 26.69; 95% CI 11.15–70.81). In contrast, tumor size was not associated with pathologic aggressive features on multivariate analysis (OR 0.81; 95% CI 0.54–1.22). Conclusion This study demonstrates that thyroid tumors expressing BRAF V600E mutations correlate with aggressive pathologic features more than tumors expressing RAS-like mutations. When comparing tumors with BRAF V600E and RAS-like mutations, the former were found to be smaller. As a result of this finding, this study suggests that molecular alterations may better predict aggressive pathologic features than the size of the tumor. Graphical Abstract
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".