Cervical cancer screening outcomes among First Nations and non‐First Nations women in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Cervical cancer disproportionately affects First Nations women in Canada but there is limited information on their participation in organized cervical cancer screening programs. METHODS: This co-led retrospective cohort study linked population-based Alberta Cervical Cancer Screening Program point of care data with First Nations identifiers. This Screening Program database includes cervical cancer screening history, screen test results, colposcopy procedure findings, and pathology results for all women in Alberta. First Nations identifiers were obtained from Alberta Health who steward these data on their behalf. Data were available from 2012 to 2018 for women 25 - 69 years of age who were age eligible to participate in cervical cancer screening. Screening participation and retention rates, and screening outcomes were compared between First Nations and non- First Nations women using descriptive statistics with trends estimated using joinpoint models. RESULTS: Age standardized screening participation and retention rates of First Nations women were lower than those for the non-First Nations women, with an average difference of 13.9 % lower for participation rates (95 % confidence interval = 12.9-14.8 %; P <.0001) and 7.2 % for retention rates (95 % confidence interval = 2.2 % to 12.72; P = 0.013). First Nations women consistently had higher percentages of high risk (high-grade squamous intraepithelial lesion, atypical glandular cells, atypical squamous cells where HSIL cannot be excluded, Carcinoma in situ) abnormal cytology tests than non-First Nations women. CONCLUSION: Identifying where inequities were found in cervical cancer screening participation and retention in this study is the first step to reduce the disproportionate burden of cervical cancer for First Nations women in Canada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".