Factors Associated with Oral Cancerous and Precancerous Lesions in an Underserved Community: A Cross-Sectional Study
Bibliographic record
Abstract
Street-involved people with limited access to regular healthcare have an increased risk of developing oral cancer and a lower survival rate. The objective of this study was to measure the prevalence of oral cancerous/precancerous lesions and determine their associated risk factors in a high-risk, underserved population. In this cross-sectional study, English-speaking adults aged 18 years and older living in a marginalized community in Edmonton were recruited from four non-profit charitable organizations. Data were collected through visual oral examinations and a questionnaire. Descriptive statistics, chi-squared tests, and logistic regressions were applied. In total, 322 participants with a mean (SD) age of 49.3 (13.5) years completed the study. Among them, 71.1% were male, 48.1% were aboriginal, and 88.2% were single. The prevalence of oral cancerous lesions was 2.4%, which was higher than the recorded prevalence in Canada (0.014–1.42: 10,000) and in Alberta (0.011–1.13: 10,000). The clinical examinations indicated that 176 (54.7%) participants had clinical inflammatory changes in their oral mucosa. There was a significant association between clinical inflammatory oral lesions and oral cancerous/precancerous lesions (p < 0.001). Simple logistic regression showed that the risk of the presence of oral cancerous/precancerous lesions was two times higher in participants living in a shelter or on the street than in those living alone (OR = 2.06; 95% CI: 1.15–3.82; p-value: 0.021). In the multiple logistic regression analysis, the risk of oral cancerous/precancerous lesions was 1.68 times higher in participants living in a shelter or on the street vs. living alone after accounting for multiple predictors (OR = 1.67; 95% CI: 1.19–2.37; p-value: 0.022). The results demonstrated a high prevalence of cancerous/precancerous lesions among the study participants, which was significantly associated with clinical inflammatory oral lesions. The evidence supports the need for developing oral cancer screening and oral health promotion strategies in underserved communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".