Aptima HPV E6/E7 mRNA Test Is as Sensitive as Hybrid Capture 2 Assay but More Specific at Detecting Cervical
Bibliographic record
Abstract
Detection of human papillomavirus (HPV) E6/E7 oncogene expression may be more predictive of cervical cancer risk than testing for HPV DNA. The Aptima HPV test (Gen-Probe) detects E6/E7 mRNA of 14 oncogenic types. Its clinical performance was compared with that of the Hybrid Capture 2 DNA test (HC2; Qiagen) in women referred for colposcopy and those routinely screened. Aptima was also compared with the PreTect HPV-Proofer E6/E7 mRNA assay (Proofer; Norchip) in the referral population. Cervical specimens collected in PreservCyt (Hologic Inc.) were processed for HPV detection and genotyping with the Linear Array (LA) method (Roche Molecular Diagnostics, Laval, Quebec, Canada). Histology-confirmed high-grade cervical intraepithelial neoplasia (CIN 2) or worse (CIN 2) served as the disease endpoint. On the basis of 1,418 referral cases (CIN 2, n 401), the sensitivity of Aptima was 96.3 % (95 % confidence interval [CI], 94.4, 98.2), whereas it was 94.3 % (95 % CI, 92.0, 96.6) for HC2. The specificities were 43.2 % (95 % CI, 40.2, 46.2) and 38.7% (95 % CI, 35.7, 41.7), respectively (P < 0.05). In 1,373 women undergoing routine screening (CIN 2, n 7),
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".