Association of <scp>HPV35</scp> with cervical carcinogenesis among women of African ancestry: Evidence of viral‐host interaction with implications for disease intervention
Bibliographic record
Abstract
HPV35 has been found in only ∼2% of invasive cervical cancers (ICC) worldwide but up to 10% in Sub-Saharan Africa, warranting further investigation and consideration of impact on preventive strategies. We studied HPV35 and ethnicity, in relation to the known steps in cervical carcinogenesis, using multiple large epidemiologic studies in the U.S. and internationally. Combining five U.S. studies, we measured HPV35 positivity and, in Northern California, observed HPV35 type-specific population prevalence and estimated 5-year risk of developing precancer when HPV35-positive. HPV35 genetic variation was examined for differences in carcinogenicity in 1053 HPV35+ cervical specimens from a U.S. cohort and an international collection. African-American women had more HPV35 (12.1% vs 5.1%, P < .001) and more HPV35-associated precancers (7.4% vs 2.1%, P < .001) compared to other ethnicities. Precancer risks after HPV35 infection did not vary by ethnicity (global P = .52). The HPV35 A2 sublineage showed an increased association with precancer/cancer in African-Americans (OR = 5.6 vs A1, 95% CI = 1.3-24.8) and A2 was more prevalent among ICC in Africa than other world regions (41.9% vs 10.4%, P < .01). Our analyses support a strong link between HPV35 and cervical carcinogenesis in women of African ancestry. Current HPV vaccines cover the majority of cervical precancer/cancer across all ethnic groups; additional analyses are required to determine whether the addition of HPV35 to the already highly effective nine-valent HPV vaccine would provide better protection for women in Africa or of African ancestry.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".