Influence of Grading on Management and Outcome in Mucoepidermoid Carcinoma of the Parotid—A Multi‐institutional Analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate clinical outcome of low (G1), intermediate (G2), and high-(G3) grade mucoepidermoid carcinomas (MEC) of the parotid gland. STUDY DESIGN: Retrospective chart review including 212 patients. Clinicopathological data was statistically analyzed regarding grading, overall survival (OS), disease-free survival (DFS) and disease-specific survival (DSS). RESULTS: 105 (49.5%) G1, 73 (34.5%) G2, and 34 (16%) G3 MEC were included and 56 (26.4%) patients presented with neck node metastases. The risk of occult nodal metastases was significantly associated with grading and increased from 9.2% in G1 to 26.7% and 27.8% in G2 and G3 tumors, respectively (p = 0.008). Elective periparotid and cervical lymph node dissection was performed in 170 (80.2%) and 70 (33%) patients, respectively. All patients with positive periparotid nodes when subjected to an additional neck dissection had associated cervical neck node involvement (p < 0.001). Grading was an independent significant prognostic factor for OS (HR 4.05; 95%CI: 1.15-14.35; p = 0.030) and DSS (HR 17.35; 95%CI: 1.10-273.53; p = 0.043). In a subgroup analysis, elective neck dissection (END) was also significantly associated with a better DFS (p = 0.041) in neck node-negative G1 MECs. CONCLUSION: The risk of occult nodal metastasis in intermediate-grade MEC is as high as in high-grade MEC and that END in G1 tumors is associated with a prolonged DFS. Additionally, periparotid node involvement seems to be a predictor for positive neck node involvement. This study presents some preliminary data to consider END in clinically neck node negative patients with parotid MEC; however, larger series are needed. LEVEL OF EVIDENCE: 3 Laryngoscope, 133:124-132, 2023.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".