DNA ploidy compared with human papilloma virus testing (Hybrid Capture II) and conventional cervical cytology as a primary screening test for cervical high‐grade lesions and cancer in 1555 patients with biopsy confirmation
Bibliographic record
Abstract
BACKGROUND: Because 80% of cervical cancers arise in low-resource settings, many inexpensive strategies are being tested. In that spirit, the authors are testing large-scale genomic or DNA ploidy measurements as an inexpensive and semiautomated strategy. METHODS: Patients entered either a screening or diagnostic study of several optical technologies: quantitative cytology, quantitative histopathology, and fluorescence and reflectance spectroscopy using a point probe, a multispectral digital colposcope, or a combination of the two. We calculated sensitivities, specificities, positive and negative predictive values, and their confidence interval testing conventional cytology, Hybrid Capture (HC) II testing, and DNA ploidy measured on the Feulgen-stained quantitative Pap smear. RESULTS: The current investigation reports on 1555 patients for whom colposcopically directed biopsies were read 3 times by study pathologists. The final histopathologic diagnosis was high grade (cervical intraepithelial neoplasia [CIN] 2, CIN 3, carcinoma in situ [CIS], and cancer) in 16% of patients. Using high-grade squamous intraepithelial lesions (SILs) histopathology as the threshold and gold standard, the sensitivity and specificity, respectively, were: 0.47 and 0.96 for conventional cytology, 0.91 and 0.80 for HC II, and 0.59 and 0.93 for DNA ploidy. The positive and negative predictive values (PPV, NPV) for conventional cytology were 0.70 and 0.90, 0.46 and 0.98 for HC II, and 0.63 and 0.92 for DNA ploidy. CONCLUSIONS: DNA ploidy shows comparable sensitivity, specificity, PPV, and NPV values to conventional cytology and HC II. Unlike conventional cytology, DNA ploidy is semiautomated and can be performed in less than 8 hours. Cost effectiveness studies are under way, but in the authors' laboratory DNA ploidy is inexpensive.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".