MassARRAY Spectrometry Is More Sensitive than PreTect HPV-Proofer and Consensus PCR for Type-Specific Detection of High-Risk Oncogenic Human Papillomavirus Genotypes in Cervical Cancer
Bibliographic record
Abstract
Type-specific detection of human papillomavirus (HPV) is indicated for better risk stratification and clinical management of women testing positive for HPV and for epidemiologic surveillance. MassARRAY spectrometry (MassARRAY; Sequenom) is a novel method for type-specific detection of 15 high-risk oncogenic HPV types: HPV-16, -18, -31, -33, -35, -39, -45, -51, -52, -56, -58, -59, -66, -68, and -73. PreTect HPV-Proofer (Proofer; Norchip) is a type-specific assay that detects E6/E7 mRNA from five high-risk oncogenic HPV types: HPV-16, -18, -31, -33, and -45. The performance of these tests for type-specific identification of HPV was assessed with cervical specimens from 192 cases of cervical cancer in comparison with consensus MY09/MY11 PCR followed by nucleotide sequencing (consensus PCR). The overall HPV detection rates were 94.8% (95% confidence interval [CI], 91.7, 97.9), 83.3% (95% CI, 78.1, 88.5), and 86.5% (95% CI, 81.7, 91.3) for MassARRAY, Proofer, and consensus PCR, respectively. All tests were negative in six (3.1%) of the 192 cases. Considering only the specimens that contained at least one of the five types targeted by Proofer, the detection rates were 96.6%, 91.4%, and 86.9% for MassARRAY, Proofer, and consensus PCR, respectively. MassARRAY detected multiple infections in 14.1%, Proofer detected multiple infections in 3.6%, and consensus PCR failed to detect any multiple infections. The agreement was highest at 86.0% (kappa = 0.76) between MassARRAY and Proofer and lowest at 81.8% (kappa = 0.69) between Proofer and consensus PCR. In conclusion, MassARRAY is a highly sensitive and accurate method for type-specific detection of oncogenic HPV in cervical cancer, with Proofer showing impressive performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".