Comparison of anal cancer screening strategies including standard anoscopy, anal cytology, and HPV genotyping in HIV-positive men who have sex with men
Bibliographic record
Abstract
BACKGROUND: There is no consensus on screening strategy of high-grade intraepithelial neoplasia (HGAIN). Guidelines range from clinical examination with digital anorectal examination followed by standard anoscopy (SA), to anal cytology (Pap)+/- HPV genotyping. We compared screening strategy yields based on Pap, SA, and HPV-16 genotyping alone or in combination in HIV-MSM. METHODS: Pap, SA, and HPV-16 genotyping were performed in all HIV-MSM attending a first anal cancer screening consultation in Paris, France. High-resolution anoscopy, the gold standard to detect HGAIN, was performed in the case of HPV-16 positivity or abnormal cytology. Yield was defined as the number of patients with HGAIN relative to the total number of patients screened. RESULTS: On 212 patients, the complete strategy (SA + Pap + HPV genotyping) yield (12.7%) was significantly higher than that of SA (3.3%, p < 0.001) and HPV-16 alone (6.6%, p < 0.05). Although none of the other strategies were significantly different from the complete strategy, Pap + HPV-16 and Pap + SA had closer yields (about 11%), with OR = 0.83 (95% CI [0.44;1.57]) and 0.87 (95% CI [0.46;1.64]), respectively. CONCLUSIONS: Pap combined with HPV-16 genotyping or SA tended towards higher yields compared to Pap alone, and closer to that of the complete strategy.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".