Evaluation of a New APTIMA Specimen Collection and Transportation Kit for High-Risk Human Papillomavirus E6/E7 Messenger RNA in Cervical and Vaginal Samples
Bibliographic record
Abstract
BACKGROUND: An APTIMA specimen collection and transportation (SCT) kit was developed by Hologic/Gen-Probe. OBJECTIVES: To compare cervical SCT samples to PreservCyt and SurePath samples and self-collected vaginal samples to physician-collected vaginal and cervical SCT samples. To determine ease and comfort of self-collection with the kit. STUDY DESIGN: Each woman (n = 580) self-collected a vaginal SCT, then filled out a questionnaire (n = 563) to determine ease and comfort of self-collection. Colposcopy physicians collected a vaginal SCT and cervical PreservCyt, SCT, and SurePath samples. Samples were tested by APTIMA HPV (AHPV) assay. RESULTS: Agreement between testing of cervical SCT and PreservCyt was 91.1% (κ = 0.82), and that of SurePath samples was 86.7% (κ = 0.72). Agreement of self-collected vaginal SCT to physician-collected SCT was 84.7% (κ = 0.68), and that of self-collected vaginal to cervical SCT was 82.0% (κ = 0.63). For 30 patients with CIN2+, AHPV testing of cervical SCT was 100% sensitive and 59.8% specific compared with PreservCyt (96.6% and 66.2%) and SurePath (93.3% and 70.9%). Vaginal SCT sensitivity was 86.7% for self-collection and 80.0% for physician collection. Most patients found that vaginal self-collection was easy, 5.3% reported some difficulty, and 87.6% expressed no discomfort. CONCLUSIONS: Cervical samples collected with the new SCT kit compared well to traditional liquid-based samples tested by AHPV. Although there was good agreement between self-collected and physician-collected samples with the SCT, in a limited number of 30 women, vaginal sampling identified fewer with CIN2+ precancerous cervical lesions than cervical SCT sampling. Comfort, ease of use, and detection of high-risk HPV demonstrated that the kit could be used for cervical and vaginal sampling.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".