Body mass index and prognosis in patients with head and neck cancer
Bibliographic record
Abstract
BACKGROUND: Body mass index (BMI) has been associated variably with head and neck cancer outcomes. We evaluated the association between BMI at either diagnosis or at early adulthood head and neck cancer outcomes. METHODS: Patients with invasive head and neck squamous cell cancer at Princess Margaret Cancer Centre in Toronto, Canada, were surveyed on tobacco and alcohol exposure, performance status, comorbidities, and BMI at diagnosis. A subset also had data collected for BMI at early adulthood. RESULTS: With a median follow-up of 2.5 years, in 1279 analyzed patients, being overweight (hazard ratio [HR], 0.55; 95% confidence interval [CI], 0.4-0.8; p = .001) at diagnosis was associated with improved survival when compared with individuals with normal weight. In contrast, underweight patients at diagnosis were associated with a worse outcome (HR, 1.89; 95% CI, 1.2-3.1; p < .01). CONCLUSION: Being underweight at diagnosis was an independent, adverse prognostic factor, whereas being overweight conferred better prognosis. BMI in early adulthood was not associated strongly with head and neck cancer outcomes. © 2017 Wiley Periodicals, Inc. Head Neck 39: 1226-1233, 2017.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".