A comparison of published head and neck stage groupings in carcinomas of the tonsillar region
Bibliographic record
Abstract
BACKGROUND: The combination of T, N, and M classifications into stage groupings was designed to facilitate a number of activities including: the estimation of prognosis and the comparison of therapeutic interventions among similar groups of cases. The authors tested the UICC/AJCC 5th edition stage grouping and seven other TNM-based groupings proposed for head and neck cancer to determine their ability to meet these expectations in a specific site: carcinoma of the tonsillar region. METHODS: The authors defined four criteria to assess each stage grouping scheme: 1) The subgroups defined by T and N comprising a given group within a grouping scheme have similar survival rates (hazard consistency); 2) The survival rates differ across the groups (hazard discrimination); 3) The prediction of cure is high (outcome prediction); and 4) The distribution of patients among the groups is balanced. The authors identified or derived a measure for each criterion and the findings were summarized using a scoring system. The range of scores was from 0 (best) to 7 (worst). Data were from a retrospective chart review on 642 cases of carcinoma of the tonsillar region treated with radiotherapy for cure at the Princess Margaret Hospital from 1970-1991. None of the patients had distant metastases. RESULTS: The scheme proposed by Synderman and Wagner, which was published in Otolaryngology Head and Neck Surgery in 1995 (vol.112, pages 691-4), scored best at 1.2. The UICC/AJCC scheme scored worst at 6.1. The hazard consistency ranged from a 3.1% average survival difference to 6.7% across the 8 schemes. The hazard discrimination measure varied by 28% from the best to worst scheme. Prediction varied by up to almost twofold across the schemes assessed. The distribution of patients varied from expected by between 0.13% and 0.57%. CONCLUSION: UICC/AJCC stage groupings were defined without empirical investigation. When tested, this scheme did not perform as well as any of seven empirically-derived schemes the authors evaluated. The results of the current study suggest that the usefulness of the TNM system can be enhanced by optimizing the design of stage groupings through empirical investigation.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".