Cervical cancer screening pathways in France in 2015–2021, a nationwide study based on medico-administrative data
Bibliographic record
Abstract
To better document cervical cancer screening (CCS) pathways, the purpose of our study was to examine CCS pathways among women who had undergone a screening test (opportunistic or organised programme), based on real-life data over a 7-year period. This study used data from the French national health care database (SNDS), which covers almost 100 % of the French population of around 66 million inhabitants. Data from 2015 to 2021 were extracted. More than one quarter (27 %) of women who were at least 25 years old in 2015 and up to 65 years old in 2021 were not screened over the 2015-2021 period. Compared to women who had undergone screening at least once, women who were not screened were older (36 % vs. 23 % in the 50-59 years age group in 2015) and lived in the most deprived urban areas (21 % vs 16 % for less and most deprived respectively). 57 % of women underwent screening within recommended intervals, 13 % of women were under-screened, and 30 % were overscreened. Overall, our study identified that, in 2021, women who participated in the French organised screening programme were less likely to be screened within the recommended interval over the 7-year period. These analyses need to be continued over time in order to assess whether the programme helps reintegrate women into the screening process.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".