A Multicountry Evaluation of careHPV Testing, Visual Inspection With Acetic Acid, and Papanicolaou Testing for the Detection of Cervical Cancer
Bibliographic record
Abstract
OBJECTIVE: This study evaluates the feasibility and performance of careHPV, a novel human papillomavirus (HPV) DNA test, when used for screening women for cervical cancer in low-resource settings. METHODS AND MATERIALS: Clinician-collected (cervical) and self-collected (vaginal) careHPV specimens, visual inspection with acetic acid (VIA), and Papanicolaou test were evaluated among 16,951 eligible women in India, Nicaragua, and Uganda. Women with positive screening results received colposcopy and histologic follow-up as indicated. The positivity of each screening method was calculated overall, by site, and age. In addition, the clinical performance of each screening test was determined for detection of cervical intraepithelial neoplasia (CIN) grade 2 (CIN2+) and CIN grade 3. RESULTS: Moderate or severe dysplasia or cancer (taken together as CIN2+) was diagnosed in 286 women. The positivity rate ranged between 2.4% to 19.6% for vaginal careHPV, 2.9% to 20.2% for cervical careHPV, 5.5% to 34.4% for VIA, and 2.8% to 51.8% for Papanicolaou test. Cervical careHPV was the most sensitive for CIN2+ (81.5%; 95% confidence interval [CI], 76.5-85.8) and CIN grade 3 (85.3%; 95% CI, 78.6-90.6) at all sites, followed by vaginal careHPV (69.6% and 71.3%, respectively). The sensitivity of VIA ranged from 21.9% to 73.6% and Papanicolaou test from 40.7% to 73.7%. The pooled specificities of cervical careHPV, vaginal careHPV, VIA, and Papanicolaou test were 91.6%, 90.6%, 84.2%, and 87.7%, respectively. CONCLUSIONS: careHPV performed well in large multicountry demonstration studies conducted in resource-limited settings that have not previously been conducted this type of testing; its sensitivity using cervical samples or vaginal self-collected samples was better than VIA or Papanicolaou test. The feasibility of using careHPV in self-collected vaginal samples opens the possibility of increasing coverage and early detection in resource-constrained areas.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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 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".