Human Papillomavirus 16 E6 Antibodies in Individuals without Diagnosed Cancer: A Pooled Analysis
Bibliographic record
Abstract
BACKGROUND: The increasing incidence of oropharyngeal cancer in many developed countries has been attributed to human papillomavirus type 16 (HPV16) infections. Recently, HPV16 E6 serology has been identified as a promising early marker for oropharyngeal cancer. Therefore, characterization of HPV16 E6 seropositivity among individuals without cancer is warranted. METHODS: A total of 4,666 controls were pooled from several studies of cancer and HPV seropositivity, all tested within the same laboratory. HPV16 E6 seropositive controls were classified as having (i) moderate [mean fluorescent intensity (MFI) ≥ 484 and <1,000] or (ii) high seroreactivity (MFI ≥ 1,000). Associations of moderate and high HPV16 E6 seroreactivity with (i) demographic risk factors; and seropositivity for (ii) other HPV16 proteins (E1, E2, E4, E7, and L1), and (iii) E6 proteins from non-HPV16 types (HPV6, 11, 18, 31, 33, 45, and 52) were evaluated. RESULTS: Thirty-two (0.7%) HPV16 E6 seropositive controls were identified; 17 (0.4%) with moderate and 15 (0.3%) with high seroreactivity. High HPV16 E6 seroreactivity was associated with former smoking [odds ratio (OR), 5.5; 95% confidence interval (CI), 1.2-51.8], and seropositivity against HPV16 L1 (OR, 4.8; 95% CI, 1.3-15.4); E2 (OR, 7.7; 95% CI, 1.4-29.1); multiple HPV16 proteins (OR, 25.3; 95% CI, 2.6-119.6 for three HPV16 proteins beside E6) and HPV33 E6 (OR, 17.7; 95% CI, 1.9-81.8). No associations were observed with moderate HPV16 E6 seroreactivity. CONCLUSIONS: High HPV16 E6 seroreactivity is rare among individuals without diagnosed cancer and was not explained by demographic factors. IMPACT: Some HPV16 E6 seropositive individuals without diagnosed HPV-driven cancer, especially those with seropositivity against other HPV16 proteins, may harbor a biologically relevant HPV16 infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".