HPV DNA testing with cytology triage in cervical cancer screening: Influence of revealing HPV infection status
Bibliographic record
Abstract
BACKGROUND: Knowledge of cervical human papillomavirus (HPV) status might influence a cytotechnician's assessment of cellular abnormalities. The authors compared original cytotechnicians' Papanicolaou (Pap) readings for which HPV status was concealed with Pap rereads for which HPV status was revealed separately for 3 screening populations. METHODS: Previously collected cervical Pap smears and clinical data were obtained from the Canadian Cervical Cancer Screening Trial (study A), the Democratic Republic of Congo Community-Based Screening Study (study B), and the Brazilian Investigation into Nutrition and Cervical Cancer Prevention (study C). Smears were reread with knowledge of HPV status for all HPV-positive women as well as a sample of HPV-negative women. Diagnostic performance of Pap cytology was compared between original readings and rereads. RESULTS: A total of 1767 Pap tests were reread. Among 915 rereads for HPV-positive women, the contrast between "revealed" and "concealed" Pap readings demonstrated revisions from negative to positive results for 109 women (cutoff was atypical squamous cells of undetermined significance or worse) and 124 women (cutoff was low-grade squamous intraepithelial lesions [LSIL] or worse). For a disease threshold of cervical intraepithelial neoplasia of grade 2 or worse, specificity significantly declined at the atypical squamous cells of undetermined significance cutoff for studies A (86.6% to 75.3%) and C (42.5% to 15.5%), and at the LSIL cutoff for study C (61.9% to 37.6%). Sensitivity remained nearly unchanged between readings, except in study C, in which reread performance was superior (91.3% vs 71.9% for the LSIL cutoff). CONCLUSIONS: A reduction in the diagnostic accuracy of Pap cytology was observed when revealing patients' cervical HPV status, possibly due to a heightened awareness of potential abnormalities, which led to more false-positive results.
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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 | 0.015 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".