Decreasing incidence of cervical adenocarcinoma in Ontario: Is this related to improved endocervical Pap test sampling?
Bibliographic record
Abstract
In many developed countries, the incidence of cervical cancer has decreased. These reductions have been specific to squamous cell carcinoma (SCC) and have not included adenocarcinoma (AC). Incidence of AC has increased steadily over the last 20 years. The intent of this article is to examine trends in cervical adenocarcinoma incidence in Ontario over a 20-year period in relation to screening practices. All cases of cervical cancer between 1981 and 2002 were extracted from the Ontario Cancer Registry (a population-based, provincial-wide database). Age-standardized incidence rates were calculated overall, by broad age groups and by morphological type (SCC and AC). Time trends were assessed using JoinPoint methodology. In Ontario, opportunistic cervical cancer screening has been accompanied by significantly decreased rates of SCC since at least 1981. Conversely, the incidence of AC rose by 3.1% per year (95% CI: 1.6%, 4.6%) between 1981 and 1995, and subsequently declined by 4.0% per year (95% CI: -7.4%, -0.5%). From the mid- to late-1990s, instructions were distributed to clinicians, reinforcing the importance of dual specimen collection (i.e., using both spatula and endocervical brush). At the same time, laboratories routinely provided physicians with kits that included both spatula and brush. The subsequent decline in AC incidence may be due, in part, to improved specimen collection. As well, the decline may be partly due to increased awareness of AC precursors among cytopathologists and clinicians, and/or improvements in laboratory training and quality assurance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".