Concurrent HPV DNA testing and a visual inspection method for cervical precancer screening: A practical approach from Battor, Ghana
Bibliographic record
Abstract
Cytology-based cervical cancer screening programs have been difficult to implement and scale up in developing countries. Thus, the World Health Organization recommends a 'see and treat' approach by way of hr-HPV testing and visual inspection. We aimed to evaluate concurrent HPV DNA testing and visual inspection in a real-world low-resource setting by comparing the detection rates of concurrent visual inspection with dilute acetic acid (VIA) or mobile colposcopy and hr-HPV DNA testing to standalone hr-HPV DNA testing (using the careHPV, GeneXpert, AmpFire, or MA-6000 platforms). We further compared their rates of loss to follow-up. This retrospective, descriptive cross-sectional study included all 4482 women subjected to cervical precancer screening at our facility between June 2016 and March 2022. The rates of EVA and VIA 'positivity' were 8.6% (95% CI, 6.7-10.6) and 2.1 (95% CI, 1.6-2.5), respectively, while the hr-HPV-positivity rate was 17.9% (95% CI, 16.7-19.0). Overall, 51 women in the entire cohort tested positive on both hr-HPV DNA testing and visual inspection (1.1%; 95% CI, 0.9-1.5), whereas a large majority of the women tested negative (3588/4482, 80.1%) for both and 2.1% (95% CI, 1.7-2.6) tested hr-HPV-negative but visual inspection 'positive'. In total, 191/275 (69.5%) participants who tested hr-HPV positive on any platform, as a standalone test for screening, returned for at least one follow-up visit. In light of factors such as poor socioeconomic circumstances, additional transportation costs associated with multiple screening visits, and lack of a reliable address system in many parts of Ghana, we posit that standalone HPV DNA testing with recall of hr-HPV positives will be tedious for a national cervical cancer prevention program. Our preliminary data show that concurrent testing (hr-HPV DNA testing alongside visual inspection by way of VIA or mobile colposcopy) may be more cost-effective than recalling hr-HPV-positive women for colposcopy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".