Adherence to cervical cancer screening varies by human papillomavirus vaccination status in a high-risk population
Bibliographic record
Abstract
Cervical cancer screening has reduced the incidence of cervical cancer over the past 75 years. The primary aim of this study was to determine if women receiving Gardasil™ (HPV4 vaccine) participated in future cervical cancer screening at the same rate as that observed for unvaccinated women matched on birth year and health care campus. This is a retrospective cohort study of subjects selected from 27,786 females born from 1980 to 1992 who received health care in the Truman Medical Center safety net health system in Kansas City Missouri, USA. 1154 women 14-26 years old who received at least one dose of HPV4 vaccine between 2006 and 2009 were chosen at random from the vaccine records. 1154 randomly chosen unvaccinated women were age and health campus matched to the vaccinated women and all were followed until July 1, 2013. Women who were screened after 21 years and received three vaccine doses before 21 years, had the lowest screening rate of 24%. Their only predictive factor for screening, compared to the unvaccinated, was being closer to 21 years than 14 years at vaccination (aOR = 1.71 95% CI: 1.45, 2.00). Women vaccinated with three doses and screened at or after 21 years had the highest screening rate of 84% predicting a six-fold increase in screening participation over no vaccine received (aOR = 5.94 95% CI: 3.77, 9.35). Our results suggest that women who receive HPV4 vaccination closer to 21 years, not 14, are more likely to participate in cervical cancer screening in an underserved US population.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".