Clinical Performance of the BD Onclarity Extended Genotyping Assay for the Management of Women Positive for Human Papillomavirus in Cervical Cancer Screening
Bibliographic record
Abstract
BACKGROUND: Among women whose cervical specimens tested positive for high-risk human papillomaviruses (hrHPV) via the Hybrid Capture 2 assay in the Canadian Cervical Cancer Screening Trial (CCCaST), we assessed hrHPV genotype concordance between BD Onclarity HPV Assay and Roche's Linear Array, overall and stratified by hrHPV viral load. We also evaluated the performance of cytology, cytology combined with hrHPV genotyping (Onclarity assay) for HPV16/18 and non-HPV16/18 types, and hrHPV genotyping triage strategies for the detection of cervical intraepithelial neoplasia grade 2 or 3 and worse (CIN2+/CIN3+). METHODS: Standard measures (expected agreement, agreement, and κ values) were used to compare Onclarity to the reference test, Linear Array. Twenty-four triage strategies were evaluated by calculating their sensitivities, specificities, and positive and negative predictive values for CIN2+ and CIN3+ detection. RESULTS: Among 734 hrHPV+ samples tested, there was near perfect concordance irrespective of viral load between the Onclarity and Linear Array assays for the individual genotypes [human papillomaviruses (HPV) 16, 18, 31, 45, 51, 52] by Onclarity (κ values ranged from 0.92-0.98). Strategies with adequate specificity (>75%) and the highest sensitivities to detect CIN3+ among 617 women positive for hrHPV, were positivity to HPV16 and/or 31 (Sensitivity: 65.2%, Specificity: 76.9%) and HPV16 and/or 18 (Sensitivity: 58.7%, Specificity: 81.6%). CONCLUSIONS: While confirming the importance of HPV16, we found that HPV31 was comparable with HPV18 for the detection of CIN2/3+ in the triage of women positive for hrHPV. IMPACT: HPV31 may be an important genotype in the triage of women positive for hrHPV.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| 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".