Comparison of APTIMA HPV E6/E7 mRNA and Hybrid Capture 2 Assays using Wet and Dry Self-Collected Flocked Vaginal Swabs and PreservCyt L-Pap Samples
Bibliographic record
Abstract
Background: Performance of HPV assays on less invasive specimens can be assessed through agreement of assays and specimen types as well as the ability to identify patients with precancerous lesions. Objectives: To compare the APTIMA HPV (AHPV) E6/E7 mRNA assay to the HC2 DNA test for high risk (HR) HPV performed on PreservCyt L-Pap cervical specimens and flocked self-collected vaginal swabs (SCVS) transported to the laboratory wet or dry. Results: Testing specimens from 100 women attending a colposcopy clinic showed 90.7% (k=0.81) agreement between HC2 and AHPV assays for PreservCyt specimens. Agreement was 80.2% (K=0.80) to 88.0% (K=0.76) between L-Pap and wet and dry SCVS respectively and 89.2% (K=0.77) between the 2 SCVS by AHPV testing. For HC2, the agreement was 90.6% (k=0.81) to 89.2% (k=0.78) between L-Pap and the 2 swabs and 96.0% (k=0.90) between wet and dry swabs. Using pathology (CIN2+) as the reference standard, SCVS tested by AHPV demonstrated sensitivities of 88.8% for dry and 90% for wet SCVS, compared to 86.4% for L-Pap samples. HC2 testing of wet and dry SCVS was 70.8% sensitive compared to 94.4% for L-Pap samples. Conclusion: SCVS collected with flocked nylon swabs transported wet or dry may serve as alternative specimens for HPV testing of women who are reluctant to have a pelvic examination.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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".