The Fundamental Place of Pap Test in Iran, Does Primary HPV-Genotyping Seem Cost-Effective in Replace? A Cohort Study
Bibliographic record
Abstract
Background: Human papillomavirus (HPV) is a known risk factor for cervical cancer, and currently, primary HPV typing is recommended for screening instead of cervical cytology. However, there are limited studies on the prevalence of HPV in Iran. Methods: This cross-sectional study evaluated the liquid-based cervical smears of 700 women with no history of HPV vaccination and cervical dysplastic disease from 2017 to 2020 in Isfahan, Iran. Here, we compare the prevalence of HPV genotypes using COBAS with Pap smear cytology results in evaluating the most appropriate cervical cancer screening test. Results: The prevalence of HPV infection was 23.3%, including 8.7% with HPV 16/18 and 14.6% with other HR (high-risk) HPVs. In cytology reports, 8 out of 16 individuals with high-risk lesions were negative for any type of HPV; on the other hand, there were 129 HR HPV-positive patients out of 570 negative or low-risk Pap smear results. Conclusions: It assumed that there is no superiority for HPV genotyping over cytology or vice versa in detecting high-risk patients for cervical cancer; as only 26.8% of women with HPV show abnormal cytology; and from those with normal cytology, 17.9% were positive for HR HPV.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".