Does Histologic Grade Have a Role in the Management of Head and Neck Cancers?
Bibliographic record
Abstract
PURPOSE: High histologic grade is usually associated with a greater propensity to distant metastases (DM). Its role to predict DM in head and neck cancer is not yet defined. The aim of this study is to evaluate the role of histologic grade as an independent predictor of DM and to determine a subgroup of patients who may benefit from systemic chemotherapy. PATIENTS AND METHODS: This is a retrospective study of 1,266 consecutive patients treated by definitive or postoperative radiotherapy between 1989 and 1997. All patients received at least 50 Gy. All stages and subsites of head/neck were included. DM rates were evaluated by the Kaplan-Meier method with a subsequent Cox analysis. RESULTS: There is a strong correlation of grade with N stage (P <.000001). The metastases-free survival (MFS) was 98%, 90%, and 72% for grades 1, 2, and 3, respectively (P <.000001). In patients with N0 stage, MFS is always greater than 90%, whatever the grade. In the 222 N1 patients, MFS was more than 90% in grade 1 and 2 but dropped to 75% for grade 3 (P =.001). In patients with N2 and N3, MFS was 91%, 79%, and 59% for grades 1, 2, and 3, respectively (P =.008). The same conclusion is applicable when only patients with neck control are analyzed. In a Cox model, grade was an independent predictor of DM (P =.000001) as well as T stage (P =.003), N stage (P =.000001), and neck failure (P =.0003). Higher grade was also an independent predictor of survival (P =.02). CONCLUSION: Patients with histologic grade 1 and grade 2 (except N3) are at low risk of DM. Patients with grade 2 and N3 or patients with grade 3 and N1 to N3 have a higher risk of distant metastases and should be considered for systemic treatment.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".