Interobserver Variability in the Histopathologic Assessment of Extrathyroidal Extension of Well Differentiated Thyroid Carcinoma Supports the New American Joint Committee on Cancer Eighth Edition Criteria for Tumor Staging
Bibliographic record
Abstract
Background: Extrathyroidal extension (ETE) by papillary and follicular thyroid carcinoma can be associated with increased risk of tumor recurrence and mortality. In the seventh edition of its Cancer Staging Manual, the American Joint Committee on Cancer (AJCC) defined minimal ETE as the involvement of skeletal muscle (i.e., strap muscles) or perithyroidal soft tissue. The eighth edition of the AJCC Cancer Staging Manual has changed the criteria so that only grossly evident (macroscopic) ETE involving strap muscles (not microscopic ETE involving perithyroidal soft tissue) affects tumor staging. Summary: Concordance of identifying microscopic ETE (as well as extranodal extension by carcinoma metastatic to lymph nodes) was previously evaluated among 11 expert endocrine pathologists. The overall agreement rate was slight when rendering a diagnosis of ETE. Concordance was highest when pathologists assessed the spatial relationship of carcinoma to skeletal muscle. This article discusses the significance of these findings. It also reviews relevant anatomic and developmental considerations related to the boundaries of the thyroid. Conclusions: The results of the concordance study provide additional rationale supporting stringent criteria for diagnosing ETE, as proposed by the eighth edition of the AJCC Cancer Staging Manual. It is expected that these rigid morphologic criteria will potentially reduce interobserver variability and enhance consistency in the diagnosis and staging of thyroid carcinoma.
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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 | 0.073 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".