Pre‐ and Post‐Radiotherapy Radiologic Nodal Features and Oropharyngeal Cancer Outcomes
Bibliographic record
Abstract
OBJECTIVES: To assess the prognostic value of pre-/post-radiotherapy (pre-/post-RT) radiologic lymph node (LN) features in human papillomavirus (HPV)-positive and HPV-negative oropharyngeal carcinoma (OPC) patients treated with definitive (chemo-)RT. METHODS: Clinical node-positive OPCs treated from 2011 to 2015 were reviewed. Nodal features were reviewed by a radiologist on pre-/post-RT computed tomography (CTs). Univariable analysis calculated hazard ratio (HR) for regional failure (RF), distant metastasis (DM), and deaths. Multivariable analysis estimated adjusted HR (aHR) of significant nodal features identified in univariable analysis adjusting for confounders. RESULTS: Pre-RT CT was undertaken in 344 HPV-positive and 94 HPV-negative OPC patients, of whom 242 (70%) HPV-positive and 67 (71%) HPV-negative also had a post-RT CT. Median follow-up was 4.9 years. Pre-RT LN calcification (pre-RT_LN-cal) increased the risk of RF in HPV-negative (aHR: 5.3, P = .007) but not HPV-positive patients (P = .110). Pre-RT radiologic extranodal extension (pre-RT_rENE+) increased the risk of DM and death in both HPV-negative (DM: aHR 6.6, P < .001; death: aHR 2.1, both P = .019) and HPV-positive patients (DM: aHR 4.9; death: aHR 3.0, both P < .001). Increased risk of RF occured with < 20% post-RT LN size reduction in both HPV-negative (HR 6.0, P = .002) and HPV-positive cases (HR 3.0, P = .049). Post-RT_LN-cal did not affect RF, DM, or death regardless of tumor HPV status (all P > .05). CONCLUSION: Pre-RT_LN-cal is associated with higher RF risk in HPV-negative but not in HPV-positive patients. Pre-RT_rENE increases risk of DM and death regardless of tumor HPV status. Minimal post-RT LN size reduction (< 20%) increases risk of RF in both diseases. Post-RT_LN-cal + has no apparent influence on outcomes in either disease. LEVEL OF EVIDENCE: 4 (a single institution case-control series) Laryngoscope, 131:E1162-E1171, 2021.
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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 | 0.000 |
| 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) | 0.000 | 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".