Cervical cancer screening uptake among HIV-positive women in Ontario, Canada: A population-based retrospective cohort study
Bibliographic record
Abstract
Cervical cancer caused by oncogenic types of the human papillomavirus (HPV) is of concern among HIV-positive women due to impairment of immune responses required to control HPV infection. Our objectives were to describe patterns of cervical cancer screening using Pap cytology testing among HIV-positive women in Ontario, Canada from 2008 to 2013 and to identify factors associated with adequate screening. We conducted a retrospective, population-based cohort study among screen-eligible HIV-positive women using provincial administrative health data. We estimated annual proportions tested and reported these with 95% confidence intervals (CI). Next, using person-years as the unit of analysis, we identified factors associated with annual Pap testing using log-binomial regression. A total of 2271 women were followed over 10,697 person-years. In 2008, 34.0% (95%CI 31.1-37.0%) had a Pap test. By 2013, the proportion of HIV-positive women tested was 25.9% (95%CI 23.6-28.2%). Women who were most likely to undergo testing were younger, were immigrants from countries with generalized HIV epidemics, lived in the highest income neighbourhoods, had a female primary care physician, had two or more encounters per year with an infectious disease or internal medicine specialist, and had greater comorbidity. Nearly three in four HIV-positive women were under-screened despite all having universal insurance for medically-necessary services. Annual Pap testing decreased following the 2011-2013 release of new guidelines for a lengthened screen interval for average risk women and a billing disincentive. Clinic-based intervention such as physician alerts or reminders may be needed to improve screening coverage among HIV-positive women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".