p53 polymorphism in codon 72 and risk of human papillomavirus-induced cervical cancer: effect of inter-laboratory variation
Bibliographic record
Abstract
An association between codon-72 p53 polymorphism and risk of human papillomavirus (HPV)-induced cervical cancer has been found recently, but it has been difficult to replicate. In this study, we assess the impact of inter-laboratory variation in p53 genotyping on the validity of the proposed association. DNA specimens were randomly selected from 54 invasive, squamous cell carcinoma cases, 52 HPV-negative, and 39 HPV-positive controls from a previous case-control study in Brazil. Codon-72 polymorphism was blindly analyzed in three different laboratories. We calculated age- and race-adjusted odds ratios (OR) and 95% confidence intervals (CI) using logistic regression for gauging the association between p53 polymorphism and cervical cancer risk. The proportions of the Arg/Arg, Arg/Pro, and Pro/Pro genotypes varied substantially among laboratories with Kappa coefficients in the 0.49-0.63 range. When disagreement between labs was allowed, the OR for the Arg/Arg genotype, compared to other forms, was as low as 1.5 (95% CI: 0.5-3. 9). In contrast, the OR increased to 8.0 (95% CI: 2.3-28.5) after exclusion of discordant genotypes. Restricting the comparison to HPV-positive controls increased the magnitude of the relation appreciably. After exclusion of all discordant diagnoses, the OR was 21.5 (95% CI: 3.4-137.8), whereas with disagreed genotypes the association was not significant (OR = 2.9, 95% CI: 0.7-11.9). Homozygous codon-72 p53-Arg apparently confers a higher susceptibility to HPV-associated cervical tumorigenesis. However, exposure misclassification consequent to inter-laboratory variation in protocols may affect the ability to detect the association.
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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 | 0.000 |
| 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) | 0.001 | 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 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".