Hybrid Capture Human Papillomavirus Testing as an Adjunct to the Follow-Up of Patients with ASCUS and LGSIL Pap Smears: A Study of a Screening Population
Bibliographic record
Abstract
OBJECTIVES: We set out to evaluate Hybrid Capture (Digene Corporation, Silver Spring, MD) testing for human papillomavirus (HPV) in the management of a screening population with atypical squamous cells of undetermined significance (ASCUS) or low-grade squamous intraepithelial lesion (LGSIL). METHODS: A total of 619 patients with ASCUS or LGSIL Papanicolaou smears were tested for high-risk HPV types. They then were followed at 6-month intervals with Papanicolaou smears and repeat HPV testing. Patients with persistent or progressive disease were referred for colposcopy. HPV results were compared to the most significant follow-up cytological or colposcopic diagnosis to determine whether Hybrid Capture HPV testing was predictive of outcome. A cost analysis was performed. RESULTS: Follow-up of 12 to 30 months was available for 471 patients (76.1%). Outcome diagnoses for 190 patients who initially tested HPV-positive were as follows: 49% benign, 14% ASCUS, 19% LGSIL, 18% HGSIL, and 0.5% cancer. For 281 patients who initially tested HPV-negative, outcomes were 77% benign, 14% ASCUS, 6% LGSIL, 2% HGSIL, and 0.3% cancer. Twenty-six of the patients with HGSIL had two or more HPV tests, and all these patients had at least one positive result. CONCLUSIONS: Hybrid Capture testing for high-risk HPV types was predictive of which patients presenting with ASCUS/LGSIL would persist or progress to HGSIL (p < .001). The cost of adding Hybrid Capture testing was intermediate between the cost of cytological follow-up and referral of all patients with ASCUS/LGSIL to 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".