Impact of contralateral lymph nodal involvement and extranodal extension on survival of surgically managed HPV-positive oropharyngeal cancer staged with the AJCC eighth edition
Bibliographic record
Abstract
OBJECTIVES: Contralateral lymph node (LN) involvement is a prognostic factor in clinical staging of oropharyngeal squamous cell carcinoma (OPSCC), while pathologic nodal staging in the AJCC 8th edition for human papillomavirus-mediated OPSCC (HPV + OPSCC) focuses exclusively on the number of involved LNs (pLN+). This study assessed if the presence of contralateral pLN+ adds prognostic importance to the number of pLN+. MATERIALS AND METHODS: The National Cancer Database was queried for pLN+ HPV + OPSCC treated with surgery with 10 or more LN dissected. Data were evaluated with Cox regression, propensity score matching (PSM), and Kaplan-Meier overall survival (OS) analysis. RESULTS: Of 3407 patients, 152 (4.5%) patients had contralateral pLN+. Subjects with contralateral pLN+ had higher pT/pN stage, more positive margins, extranodal extension (ENE), and lymphovascular invasion (LVI) (all p < 0.05). On univariate analysis, contralateral pLN+ trended toward worse OS (HR 1.58, 95% CI 0.98-2.55, p = 0.061). In the multivariable model (controlling for age, comorbidities, T-stage, N-stage, LN size, ENE, LVI, margin status and adjuvant therapy), LN laterality had no impact on OS (HR 0.87, 95% CI 0.52-1.45, p = 0.520). Further PSM analysis confirmed that contralateral pLN+ is not associated with OS in this population (HR 0.79, 95% CI 0.41-1.53, p = 0.494). CONCLUSION: This study supports the AJCC 8th edition pathologic staging for HPV + OPSCC by observing that LN laterality is not associated with OS. ENE was associated with inferior OS and should be considered for future staging systems. Further study should be directed at the importance of nodal size in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".