Human Papillomavirus Infection and Incidence of Squamous Cell and Basal Cell Carcinomas of the Skin
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Although infection with human papillomaviruses (HPVs) is a major risk factor for several epithelial cancers, an etiologic relationship between HPV and keratinocyte cancers, such as squamous cell carcinomas (SCCs) and basal cell carcinomas (BCCs), remains unclear. METHODS: In a population-based case-control study of 252 SCC case patients, 525 BCC case patients, and 461 control subjects, we used multiplex serology to detect antibodies in plasma samples against 16 HPV types from phylogenetic genera alpha, beta, and mu. Multiplex serology is a new method that is based on fluorescent bead technology and allows simultaneous detection of antibodies against up to 100 different in situ affinity-purified recombinant HPV proteins. Data on sun sensitivity, outdoor exposure, and other risk factors for keratinocyte cancers were collected through personal interviews. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated via unconditional logistic regression models. RESULTS: Overall, we detected HPV antibodies more frequently in SCC patients than in control subjects (OR = 1.6, 95% CI = 1.2 to 2.3), but we found no difference in HPV seropositivity between BCC case patients and control subjects (OR = 0.8, 95% CI = 0.6 to 1.1). Among HPV types, seropositivity to HPV types in genus beta (OR = 1.5, 95% CI = 1.0 to 2.1), particularly HPV 5 (OR = 1.8, 95% CI = 1.0 to 3.1), was associated with SCC risk. Individuals with tumors on chronically sun exposed sites were more likely to be seropositive for beta HPV types than individuals with SCC at other anatomic sites. The highest SCC risk was associated with positivity for multiple HPV types and, among individuals seropositive for HPV beta, a tendency to sunburn; however, the associations had limited statistical precision. CONCLUSIONS: Our findings support a role for HPV types from the genus beta in the pathogenesis of SCC.
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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 | 0.000 |
| 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 it