The role of cytology (Pap tests) and human papillomavirus testing in anal cancer screening
Bibliographic record
Abstract
OBJECTIVE: To assess anal oncogenic human papillomavirus (HPV) and anal cytology as screening tests for detecting high-grade anal intraepithelial neoplasia (AIN 2+), as this is an immediate anal cancer precursor. DESIGN: Cross-sectional study of 401 HIV-positive men who have sex with men (MSM). The endpoint was histologically confirmed AIN 2+ obtained by high-resolution anoscopy. Cytology and biopsy specimens were assigned random numbers and independently assessed by two pathologists. METHODS: We did concomitant anal cytology, anal HPV testing and HRA with directed biopsies without knowing the results of each intervention. The main outcome measures were the sensitivity, specificity, negative predictive value and positive predictive value of anal cytology and oncogenic HPV for the detection of AIN 2+. RESULTS: Cytology was abnormal in 67% of patients: high-grade squamous intraepithelial lesion, 12%; low-grade squamous intraepithelial lesion, 43% and atypical squamous cells of undetermined significance, 12%. Biopsies were abnormal in 68% of patients: AIN 2+, 25% and AIN 1, 43%. HPV was detected in 93% with multiple HPV types in 92% and oncogenic HPV types in 88%. Test performance characteristics for the detection of AIN 2+ using any abnormality on anal cytology were: sensitivity 84%, specificity 39%, negative predictive value 88% and positive predictive value 31%; using oncogenic HPV: sensitivity 100%, specificity 16%, negative predictive value 100% and positive predictive value 28%. CONCLUSION: Anal cytology and HPV detection have high sensitivity but low specificity for detecting AIN 2+. HIV-positive men who have sex with men have a high prevalence of AIN 2+ and require high-resolution anoscopy for optimal detection of high-grade anal dysplasia.
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 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 | 0.013 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".