CINtec PLUS and cobas HPV testing for triaging Canadian women referred to colposcopy with a history of low-grade squamous intraepithelial lesion: Baseline findings
Bibliographic record
Abstract
OBJECTIVE AND METHODS: CINtec PLUS and cobas HPV tests were assessed for triaging women referred to colposcopy with a history of LSIL cytology. Both tests were performed at baseline using ThinPrep cervical specimens and biopsy confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+) served as the clinical endpoint. RESULTS: In all ages, (19-76 years, n = 600), 44.3% (266/600) tested CINtec PLUS positive vs. 55.2% (331/600) HPV positive (p = 0.000). Based on 224 having biopsies, sensitivity to detect CIN2+ (n = 54) was 81.5% (44/54) for CINtec PLUS vs. 94.4% (51/54) for HPV testing (p = 0.039); specificities were, 52.4% (89/170) vs. 44.1% (75/170), respectively (p = 0.129). In women ≥30 years (n = 386), 41.2% (159/386) tested CINtec PLUS positive vs. 50.8% (196/386) HPV positive (p = 0.008). Based on 135 having biopsies, sensitivity to detect CIN2+ (n = 24) was 95.8% (23/24) for both CINtec PLUS and HPV tests; specificities were, 55.0% (61/111) vs. 50.5% (56/111), respectively (p = 0.503). CONCLUSIONS: For women referred to colposcopy with a history of LSIL cytology, CINtec PLUS or cobas HPV test could serve as a predictor of CIN2+ with high sensitivity, particularly in women ≥30 years. Either test can significantly reduce the number of women requiring further investigations and follow up in colposcopy clinics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".