Is Lower Socioeconomic Status Associated with More Advanced Thyroid Cancer Stage at Presentation? A Study in Two Canadian Centers
Bibliographic record
Abstract
BACKGROUND: Some studies have shown a higher incidence of thyroid cancer in patients with insurance coverage and higher socioeconomic status (SES), and a higher thyroid cancer stage in patients with lower SES, suggesting SES-related health disparity in thyroid cancer. However, it is not known if the same is evident under a universal healthcare system such as that in Canada. METHODS: We used data from the Canadian Thyroid Cancer Consortium, a large thyroid cancer registry that collects data from two major thyroid cancer referral centers (London, Ontario, and Halifax, Nova Scotia). We included patients who presented with thyroid cancer between 1998 and 2011. We determined age at presentation, sex, and thyroid cancer status using the American Joint Committee on Cancer (AJCC) staging criteria. Individuals' postal codes were used to retrieve data from the Canadian census for the years 1996, 2001, and 2006 to approximate household income. Ordered logistic regression was used to determine odds ratios of presenting with more advanced stage thyroid cancer as they relate to income, age, and sex. RESULTS: We included 1701 patients: 1334 cases from London and 367 from Halifax. Thyroid cancer was diagnosed more frequently in the higher SES groups (p<0.001). Compared to patients in the top income quintile, patients in the lowest and second-lowest income quintiles had significantly higher odds of having more advanced stage thyroid cancer at presentation (OR 1.58, p=0.002; 1.37, p=0.024 respectively). CONCLUSIONS: Our study suggests that, similar to countries that lack a universal healthcare system, health disparity in thyroid cancer also exists in Canada. It appears that while thyroid cancers were diagnosed more frequently in Canadian patients of higher SES, Canadian patients in the lower SES groups had more advanced stage thyroid cancer at presentation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".