C‐reactive Protein in HPV‐Positive and HPV‐Negative Oropharyngeal Cancer
Bibliographic record
Abstract
OBJECTIVE: Evaluate serum C-reactive protein (CRP) in human papillomavirus (HPV)-positive oropharynx cancer as compared with HPV-negative oropharynx cancer and determine if CRP levels were associated with overall survival and/or recurrence-free survival. STUDY DESIGN: Prospective cohort study. SETTING: Tertiary care academic cancer center between 2007 and 2010. SUBJECTS AND METHODS: Among patients with oropharynx cancer and confirmed HPV status, plasma CRP levels were measured with a high-sensitivity ELISA kit. Multivariable logistic regression analysis compared 4 categories of CRP (low, moderate, high, very high) between the HPV-positive and HPV-negative groups. Kaplan-Meier methods and Cox regression models were used to determine overall survival and recurrence-free survival by CRP level in both populations. RESULTS: Between 113 HPV-positive and 110 HPV-negative patients, CRP levels were significantly higher in the HPV-positive group, but these levels did not demonstrate a statistically significant dose-response trend. Higher CRP levels were also associated with reduced overall survival ( P = .016) and recurrence-free survival ( P < .001) within the HPV-negative group in univariable analysis; in multivariate analysis, the comparisons were not significantly different. Within HPV-positive oropharynx cancer, CRP levels were not significantly associated with overall survival or recurrence-free survival in univariable or multivariable analyses. CONCLUSION: Circulating CRP was higher in HPV-positive versus HPV-negative oropharynx cancer. Among HPV-negative patients, higher CRP levels were associated with reduced survival.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".