Screening Histories and Contact with Physicians as Determinants of Cervical Cancer Risk in Montreal, Quebec
Bibliographic record
Abstract
BACKGROUND: Cervical cancer (cca) is largely a preventable disease if women receive regular screening, which allows for the detection and treatment of preinvasive lesions before they become invasive. Having been inadequately screened is a common finding among women who develop cca. Our primary objective was to determine the Pap screening histories of women diagnosed with cca in Montreal, Quebec. Secondary objectives were to determine the characteristics of women at greatest risk of cca and to characterize the level of physician contact those women had before developing cca. METHODS: The Invasive Cervical Cancer Study, a population-based case-control study, consisted of Greater Montreal residents diagnosed with histologically confirmed cca between 1998 and 2004. Respondents to the 2003 Canadian Community Health Survey and a sample of women without cca obtained from Quebec medical billing records served as controls. RESULTS: During the period of interest, 568 women were diagnosed with cca. Immigrants and women speaking neither French nor English were at greatest risk of cca. Most of the women in the case group had been screened at least once during their lifetime (84.8%-90.4%), but they were less likely to have been screened within 3 years of diagnosis. Having received care from a family physician or a medical specialist other than a gynecologist within the 5 years before diagnosis was associated with a greater risk of cca development. CONCLUSIONS: Our findings provide evidence of the need for an organized population-based screening program. They also underscore the need for provider education to prevent missed opportunities for cca screening when at-risk women seek medical attention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".