The role of computed tomography in the T classification of laryngeal carcinoma
Bibliographic record
Abstract
BACKGROUND: The objectives of this study were 1) to describe patterns of use of computed tomography (CT) in laryngeal carcinoma, and 2) to characterize the contribution of CT to the T classification of laryngeal carcinoma. METHODS: The study population comprised 1195 patients with laryngeal carcinoma diagnosed from 1982 through 1995 chosen randomly from the Ontario provincial cancer registry. A chart review was conducted to obtain data on each case. Patient-related, tumor-related, and health-system-related factors were analyzed to identify factors associated with the use of CT. Descriptions of clinical exams and CT reports were reviewed to see how CT information modified T classification. Actuarial local control and cause specific survival curves were plotted by clinical T classification without and with CT to evaluate stage migration. The percentage of the variance in outcome explained by T classification in a Cox analysis was used to evaluate whether the prognostic accuracy of T classification was improved with the use of information from CT. RESULTS: Patients with glottic (20.1%) and supraglottic (41.7%) carcinoma underwent CT. The use of CT increased over time in glottic and supraglottic carcinoma combined from 17.2% in 1982-5 to 33.9% in 1991-5. Computed tomography was used less often in older patients with a 16% (95% confidence interval, 5-27%) decrease in the odds of having CT with each 10-year age increment. Computed tomography use varied considerably across the cancer center regions in Ontario. Computed tomography altered the T classification in 20.2% of those patients who had CT, with most being "upstages." Stage migration due to CT was demonstrated. Using information from CT in the assignment of T classification for 27.8% of this study population did not make a significant contribution to the ability of T classification to predict outcome over the entire group. CONCLUSIONS: There is large variation in the use of CT among different age groups and regions. The ability to compare outcomes by stage across geographic areas is compromised when the use of CT varies.
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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".