The utility of HPV DNA testing in triage of low-grade cytological abnormalities
Bibliographic record
Abstract
This study evaluated the usefulness of human papillomavirus (HPV) DNA testing and repeat cytology in triage of women referred to colposcopy in St. John's, Newfoundland with atypical squamous cells of undetermined significance (ASCUS) or low-grade squamous intraepithelial lesion (LSIL) cytology. Data were collected on the initial Pap abnormality that prompted referral, HPV test, repeat Pap test, and histology if biopsies were ordered. Of 447 women, 97 with ASCUS and 145 with LSIL had results for all tests. For ASCUS, HPV testing was 100% sensitive for detection of underlying high-grade intraepithelial lesions (HSIL) while reducing referrals to 44.3%. There would have been significant reductions in referrals among women ≥30 years of age (74.3%) compared to younger women (27.4%). Nevertheless, in restricting HPV testing to women aged ≥30 years, 8/16 women with underlying HSIL would not have been referred to colposcopy. Repeat cytology was less sensitive (75%) for triaging all women. For LSIL, any method would have referred approximately 60% or more if a good sensitivity was achieved in any age group. For ASCUS, HPV triage appears to be more useful than repeat cytology. No useful triage strategy was identified for LSIL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".