Clinical Evaluation of the Cartridge-Based GeneXpert Human Papillomavirus Assay in Women Referred for Colposcopy
Bibliographic record
Abstract
High-risk human papillomavirus (hrHPV) testing is now being introduced as a potential primary screening test for improved detection of cervical precancer and cancer. Current U.S. Food and Drug Administration-approved tests are batch tests that take several hours to complete. A rapid, non-batch test might permit point-of-care (POC) testing, which can facilitate same-day screen and management strategies. For a non-batch, random-access platform (GeneXpert; Cepheid, Sunnyvale, CA), a prototype hrHPV assay (Xpert) has been developed where testing for 14 hrHPV types can be completed in 1 h. In the first clinical evaluation, Xpert was compared to two validated hrHPV tests, the cobas HPV test (cobas, Roche Molecular Systems) and Hybrid Capture 2 (hc2, Qiagen), and to histologic outcomes using specimens from colposcopy referral populations at 7 clinical sites in the United States (n = 697). The sensitivity of Xpert for cervical intraepithelial neoplasia grade 2 or more severe diagnoses (CIN2+) (n = 141) was equal to that of cobas (90.8% versus 90.8%, P = 1) and greater than that of hc2 (90.8% versus 81.6%, P = 0.004). Xpert was more specific than cobas (42.6% versus 39.6%, P = 0.02) and less specific than hc2 (42.6% versus 47.7%, P < 0.001). Similar results were observed for cervical intraepithelial neoplasia grade 3 or higher (CIN3+) (n = 91). HPV16 detection by Xpert identified 41.8% of the CIN2+ specimens with a positive predictive value (PPV) of 54.6%. By comparison, HPV16 detection by cobas identified 42.6% of the CIN2+ specimens with a PPV of 55.0%. hrHPV detection by the Xpert demonstrated excellent clinical performance for identifying women with CIN2+ and CIN3+ that was comparable to that of currently available clinically validated tests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".