Adjunctive HPV In-Situ Hybridization (ISH) Assay as an Aid in the Diagnosis of Cervical Intraepithelial Neoplasia in Cervical Tissue Specimens
Bibliographic record
Abstract
The purpose of this study was to develop and analytically and functionally validate a new human papillomavirus (HPV) in-situ hybridization (ISH) assay and to determine whether the use of this assay combined with hemotoxylin and eosin (H&E) staining could potentially improve the diagnostic accuracy of interpreting cervical intraepithelial neoplasia (CIN) in human cervical tissue specimens. An automated HPV ISH assay was developed using probes that targeted the broad spectrum of HPV genotypes most commonly associated with CIN. In an exploratory study, tissue sections (n=118) were stained with H&E alone and H&E with HPV ISH and evaluated by 6 general surgical pathologists. Results were compared with diagnoses established by expert pathologists on H&E alone. The change in specificity (diagnosis of no-CIN) and sensitivity (diagnosis of CIN) using H&E plus HPV versus H&E alone was determined. The HPV ISH assay detected 21 HPV genotypes and demonstrated no cross-reactivity to Epstein-Barr virus, cytomegalovirus, herpes simplex virus (HSV)-1, HSV-2, or human placental DNA. The assay detected HPV in a range of 1 to 600 copies on CaSki, HeLa, and SiHa xenografts. Use of this assay with H&E staining improved the average diagnostic specificity of the surgical pathologists from 68.5% to 89.9% (P<0.001), with fewer false-positive CIN 1 results (122 vs. 39). The diagnostic sensitivity was similar for assessments made with H&E alone and those made with HPV plus H&E (93.1% vs. 93.6%). In conclusion, a new automated broad-spectrum HPV ISH assay combined with H&E-stained slides contributed to better ascertainment of CIN than H&E staining alone.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".