Pattern of Spread to the Lateral Neck in Metastatic Well-Differentiated Thyroid Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: There remains controversy surrounding the extent of lateral neck dissection required in patients with papillary thyroid cancer (PTC) and suspicious or confirmed metastatic lateral neck lymphadenopathy. The evidence for this clinical dilemma has never been reviewed systematically nor has there been an attempt to meta-analyze the data by lymph node levels to better characterize the pattern of spread. METHODS: This meta-analysis used MEDLINE and EMBASE including all cohort studies reporting the pattern of lateral neck disease in patients who underwent a neck dissection for clinically, radiographically, or cytologically suspicious or confirmed metastatic lymphadenopathy for PTC. Our main outcome was the number of patients with positive involvement at a given level as a percentage of the cohort of patients with positive lateral neck disease, each level being measured separately. RESULTS: Eighteen studies with a total of 1145 patients and 1298 neck dissections were included in our meta-analysis. Levels IIa and IIb had disease in 53.1% [95% confidence interval (CI) 46.6-59.5%] and 15.5% [CI 8.2-27.2%], respectively. Studies that did not distinguish between level IIa and IIb or in which both were collapsed into one category showed a total level II involvement of 53.4% [CI 49.7-57.1%]. Level III and level IV were involved in 70.5% [CI 67.0-73.9%] and 66.3% [CI 61.4-70.9%] of specimens. Studies that did not distinguish between level Va and Vb or in which both were collapsed into one category showed a total level V involvement of 25.3% [CI 20.0-31.5%]. Levels Va and Vb had positivity in 7.9% [CI 2.8-20.0%] and 21.5% [CI 7.7-47.6%], respectively, but had only three studies that could be meta-analyzed. CONCLUSIONS: This systematic review of the literature and meta-analysis of the pattern of spread indicates significant rates of lymph node metastasis to all lateral neck levels in patients with PTC with regional involvement. This evidence leads us to recommend a comprehensive selective neck dissection of levels IIa, IIb, III, IV, and Vb in patients with lateral neck disease from PTC. The evidence for level Va is lacking, as most studies did not distinguish between levels Va and Vb, and the border between the two levels was inconsistent. Future studies will need to address these sublevels separately.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.032 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".