The relationship between survival and socio-economic status for head and neck cancer in Canada
Bibliographic record
Abstract
BACKGROUND: Human papilloma virus (HPV) is emerging as the primary cause for some head and neck cancers. The objective of this study was to investigate the association between head and neck cancer (HNC) survival and socioeconomic status (SES) in Canada, and to investigate changes in the relationship between HNC survival and SES from 1992 to 2005. METHODS: Cases were drawn from the Canadian Cancer Registry (1992-2005), and were categorized into three subsites: oropharynx, oral cavity, and "other" (hypopharynx, larynx, and nasopharynx). Demographic and socioeconomic information were extracted from the Canadian Census of Population data for the study period, which included three census years: 1991, 1996 and 2001. We linked cases to income quintiles (InQs) according to patients' postal codes. RESULTS: Overall survival, without controlling for smoking, for oropharyngeal cancer increased dramatically from 1992-2005 in Canada. This increase in survival for oropharynx cancer was eliminated by the introduction of controls for smoking. Survival for all head and neck cancer subsites was strongly correlated with SES, as measured by income quintile, with lower InQ's having lower survival than higher. Lastly, the magnitude of the difference in survival between the highest and lowest income quintiles increased significantly over the time period studied for oropharynx cancer, but did not statistically significantly change for oral cavity cancer or other head and neck cancers. CONCLUSIONS: These data confirm a significant impact of socioeconomic deprivation on overall survival for head and neck cancers in Canada, and may provide indirect evidence that HPV-positive head and neck cancers are more common in higher socioeconomic groups.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".