Performance indicators in a newly established organized cervical screening programme: registry-based analysis in the Czech Republic
Bibliographic record
Abstract
In 2008, the organized Czech National Cervical Cancer Screening Programme (CNCCSP) was initiated by transformation of the existing opportunistic efforts. The aim of our study was to examine recent cervical cancer burden trends and to assess the quality of the Czech National Cervical Cancer Screening Programme using a set of standard performance indicators. Our study utilized data from the national Cervical Cancer Screening Registry and the Czech National Cancer Registry. We computed internationally accepted indicators and assessed time trends and variability among screening centres. Between 1995 and 2011, the incidence of age-standardized cervical cancer decreased by 21% (1023 cases in 2011), and the mortality decreased by 35% (399 deaths in 2011). The annual coverage of the target population by cervical screening increased to 56% in 2013 (as compared with 35% in 2001). If we consider a 2-year interval (2012-2013), the estimated coverage was 77%. Over two million women underwent screening in 2013; 96% of them had a negative result. About 0.2% of smears showed cytological signs of a high-grade intraepithelial lesion or a malignancy, and the estimated positive predictive value for advanced intraepithelial neoplasia (cervical intraepithelial neoplasia grade 2+) was 79.6%. However, performance indicators show considerable heterogeneity between screening centres. The reported values of performance indicators are in line with the results of programmes that have previously been shown to be successful in terms of decreasing the cervical cancer burden, and are promising with respect to an even more pronounced decrease in cervical cancer mortality in the near future, provided that continuous quality improvement can be maintained. Linkage studies between screening, cancer and cause-of-death registers can provide further information on screening effectiveness and validity issues.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.002 | 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".