Abstract 4223: Conducting community oral cancer screening among South Asians in British Columbia
Bibliographic record
Abstract
Abstract Introduction: Globally, more than 300,000 cases of oral cancer are diagnosed annually. South Asian countries, such as India, bear the brunt of this disease due to rampant use of chewing tobacco, betel quid and areca nut. BC has a high proportion of South Asian immigrants. Oral cancer has a high mortality rate (~50% 5-year survival) due to the advanced stage at which it is often diagnosed. It is purported that the majority of oral cancers develop from oral potentially malignant lesions (OPML). While lesions can be easily detected by oral health care providers, it can be challenging to differentiate benign lesions from OPML. DNA aneuploidy has been shown to be an effective marker to predict malignant transformation in OPML. Quantitative cytology (QC) studies DNA content (ploidy) and nuclear morphometric changes within the cell. The aim of this project is to assess the need for oral cancer screening in South Asians in BC and to validate QC as an adjunct screening device in a predominantly South Asian community screening setting to assess its effectiveness in identifying high-risk lesions among visually suspicious lesions. Methods: Demographic information (gender, age, country of birth, ethnicity, risk habit information and dental usage) were collected at the time of screening. Extraoral, intraoral and fluorescence visualization (FV) examinations were conducted. Buccal mucosal brushings were collected from each participant. Brushings were also collected from lesions or areas that had a loss of fluorescence. Thin-layer cytology slides were prepared and stained using Feulgen Eosin. Slides were scanned using the Cancer Imaging Scanner at BC Cancer using machine learning classification algorithms to identify single, in-focus epithelial nucleus. Cells are classified based on DNA ploidy and malignant associated changes. Results: 307 participants were screened of which 303 were eligible. More than 99% of the participants were South Asian or Asian. 104 (34%) lesions were documented: 45 (15%) were high risk (white or red lesions, lichen planus (LP)) and 59 (19%) were low risk (trauma, candidiasis, aphthous ulcers). Twenty participants (7%) were suspected to have high-risk OPMLs (not LP): 12 were referred directly to our Next Gen Oral Dysplasia clinic for biopsy, while 8 were reassessed at 3 weeks. Chewing tobacco was found to be strongly associated with lesion presence (p<0.01). QC analysis is ongoing for 320 samples. To date, 5 biopsies have been performed resulting in 1 mild dysplasia, 1 severe dysplasia and 3 hyperplasia. Conclusion: South Asians in BC were found to be at high risk for OPMLs. QC may help to improve the sensitivity and specificity of oral cancer screening by distinguishing false FV positive inflammatory lesions from high-risk lesions. Citation Format: Leigha D. Rock, Madhurima Datta, Denise M. Laronde, Anita Carraro, Jagoda Korbelik, Alan Harrison, Martial Guillaud. Conducting community oral cancer screening among South Asians in British Columbia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4223.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".