HIV Modifies the Effect of Tobacco Smoking on Oral Human Papillomavirus Infection
Bibliographic record
Abstract
BACKGROUND: People living with HIV (PLWH) are more likely to smoke and harbor oral human papillomavirus (HPV) infections, putting them at higher risk for head and neck cancer. We investigated effects of HIV and smoking on oral HPV risk. METHODS: Consecutive PLWH (n = 169) and at-risk HIV-negative individuals (n = 126) were recruited from 2 US health centers. Smoking history was collected using questionnaires. Participants provided oral rinse samples for HPV genotyping. We used multivariable logistic regression models with interaction terms for HIV to test for smoking effect on oral HPV. RESULTS: PLWH were more likely to harbor oral HPV than HIV-negative individuals, including α (39% vs 28%), β (73% vs 63%), and γ-types (33% vs 20%). HIV infection positively modified the association between smoking and high-risk oral HPV: odds ratios for smoking 3.46 (95% confidence interval [CI], 1.01-11.94) and 1.59 (95% CI, .32-8.73) among PLWH and HIV-negative individuals, respectively, and relative excess risk due to interaction (RERI) 3.34 (95% CI, -1.51 to 8.18). RERI for HPV 16 was 1.79 (95% CI, -2.57 to 6.16) and 2.78 for β1-HPV (95% CI, -.08 to 5.65). CONCLUSION: Results show tobacco smoking as a risk factor for oral HPV among PLWH.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".