Serologic markers of <i>Chlamydia trachomatis</i> and other sexually transmitted infections and subsequent ovarian cancer risk: Results from the <scp>EPIC</scp> cohort
Bibliographic record
Abstract
A substantial proportion of epithelial ovarian cancer (EOC) arises in the fallopian tube and other epithelia of the upper genital tract; these epithelia may incur damage and neoplastic transformation after sexually transmitted infections (STI) and pelvic inflammatory disease. We investigated the hypothesis that past STI infection, particularly Chlamydia trachomatis, is associated with higher EOC risk in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort including 791 cases and 1669 matched controls. Serum antibodies against C. trachomatis, Mycoplasma genitalium, herpes simplex virus type 2 (HSV-2) and human papillomavirus (HPV) 16, 18 and 45 were assessed using multiplex fluorescent bead-based serology. Conditional logistic regression was used to estimate relative risks (RR) and 95% confidence intervals (CI) comparing women with positive vs. negative serology. A total of 40% of the study population was seropositive to at least one STI. Positive serology to C. trachomatis Pgp3 antibodies was not associated with EOC risk overall, but with higher risk of the mucinous histotype (RR = 2.30 [95% CI = 1.22-4.32]). Positive serology for chlamydia heat shock protein 60 (cHSP60-1) was associated with higher risk of EOC overall (1.36 [1.13-1.64]) and with the serous subtype (1.44 [1.12-1.85]). None of the other evaluated STIs were associated with EOC risk overall; however, HSV-2 was associated with higher risk of endometrioid EOC (2.35 [1.24-4.43]). The findings of our study suggest a potential role of C. trachomatis in the carcinogenesis of serous and mucinous EOC, while HSV-2 might promote the development of endometrioid disease.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".