Primary hrHPV DNA Testing in Cervical Cancer Screening: How to Manage Screen-Positive Women? A POBASCAM Trial Substudy
Bibliographic record
Abstract
BACKGROUND: High-risk human papillomavirus (hrHPV) testing has higher sensitivity but lower specificity than cytology for cervical (pre)-cancerous lesions. Therefore, triage of hrHPV-positive women is needed in cervical cancer screening. METHODS: A cohort of 1,100 hrHPV-positive women, from a population-based screening trial (POBASCAM: n = 44,938; 29-61 years), was used to evaluate 10 triage strategies, involving testing at baseline and six months with combinations of cytology, HPV16/18 genotyping, and/or repeat hrHPV testing. Clinical endpoint was cervical intraepithelial neoplasia grade 3 or worse (CIN3(+)) detected within four years; results were adjusted for women not attending repeat testing. A triage strategy was considered acceptable, when the probability of no CIN3(+) after negative triage (negative predictive value, NPV) was at least 98%, and the CIN3(+) risk after positive triage (positive predictive value, PPV) was at least 20%. RESULTS: Triage at baseline with cytology only yielded an NPV of 94.3% [95% confidence interval (CI), 92.0-96.0] and a PPV of 39.7% (95% CI, 34.0-45.6). An increase in NPV, against a modest decrease in PPV, was obtained by triaging women with negative baseline cytology by repeat cytology (NPV 98.5% and PPV 34.0%) or by baseline HPV16/18 genotyping (NPV 98.8% and PPV 28.5%). The inclusion of both HPV16/18 genotyping at baseline and repeat cytology testing provided a high NPV (99.6%) and a moderately high PPV (25.6%). CONCLUSIONS: Triaging hrHPV-positive women by cytology at baseline and after 6 to 12 months, possibly in combination with baseline HPV16/18 genotyping, seems acceptable for cervical cancer screening. IMPACT: Implementable triage strategies are provided for primary hrHPV screening in an organized setting.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".