Adjunctive Human Papillomavirus Testing in the 2-Year Follow-up of Women With Low-Grade Cervical Cytologic Abnormalities: A Randomized Trial and Economic Evaluation
Bibliographic record
Abstract
Abstract Context. —Although human papillomavirus (HPV) testing may aid in managing low-grade abnormality on screening cervical cytology, patient compliance with repeat testing programs requires consideration. Objectives. —To determine effectiveness and costs of repeated Papanicolaou (Pap) test and oncogenic HPV testing for detecting cervical intraepithelial neoplasia 2 or 3. Design. —We conducted a randomized controlled trial of combined Pap test and cervical HPV testing by Hybrid Capture 1 test compared with Pap test alone; tests were performed every 6 months for up to 2 years. The study end point was colposcopic examination performed on all women at 2 years, or earlier if an HPV test was positive or if a Pap test showed high-grade squamous intraepithelial lesion. Setting. —Sixty-six community family practices. Participants. —Two hundred fifty-seven women with atypical squamous cells of undetermined significance or low-grade squamous intraepithelial lesion on screening cervical cytology. Main Outcome Measures. —Detection of histologically confirmed cervical intraepithelial neoplasia 2 or 3, fully allocated costs, and loss to follow-up. Results. —Combined Pap test and HPV testing detected 11 (100%) of 11 cases of cervical intraepithelial neoplasia 2/3, whereas Pap test alone detected 7 (63.6%) of these 11 cases ( P = .14); corresponding specificities were 39 (46.4%) of 84 and 45 (71.4%) of 63 ( P = .005). The cost-effectiveness ratio was Can $4456 per additional case of high-grade cervical intraepithelial neoplasia. Sixty-nine (26.8%) of the 257 women (24.6% combined group vs 29.1% Pap test only group, P = .41) defaulted from testing or from colposcopy when referred with an abnormal result. Conclusions. —Combined testing was more costly but may detect more cases of cervical intraepithelial neoplasia 2/3 than Pap test alone. However, poor adherence limits usefulness of a management strategy that requires repeated follow-up.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".