Comprehensive appraisal of the association between sexually transmitted infections and prostate cancer: A scoping review of empirical studies, reviews, and meta-analyses
Bibliographic record
Abstract
We performed a scoping review on the association of sexually transmitted infections (STIs) with prostate cancer and identified knowledge gaps. Searching four databases (Medline, Embase, Scopus, and Cochrane) identified 286 eligible records. Most empirical studies (n = 191) were cross-sectional (n = 66) and case-control (n = 52). The most studied STIs were human papillomavirus (HPV) (n = 82), human immunodeficiency virus (HIV) (n = 52), and herpes simplex virus (HSV) (n = 30). We included 68 narrative reviews, 10 systematic reviews, and 17 meta-analyses. Most effect estimates (odds ratios, hazard ratios, risk ratios and standardised incidence ratios) did not support an association between STIs and prostate cancer: 373 and 218 of 591 effect estimates were above and below the null, respectively, except for HIV where 74 of 108 estimates were below the null. Knowledge gaps included case-control studies, insights into HIV-related mechanisms for a lower risk for prostate cancer, studies on Mycoplasma and Ureaplasma , studies adjusting for co-infection with other STIs, and studies assessing whether STIs predispose men to a more aggressive form of prostate cancer. A key research priority identified is the need for more evidence on the biological mechanisms driving infection-mediated prostate carcinogenesis. • Sexually transmitted infection-prostate cancer associations are mostly unsupported. • Lower prostate cancer risk was reported in HIV-infected men (mechanisms uncertain). • HPV, HIV and HSV are more represented in the literature, fewer studies for bacteria. • Gaps include studies adjusting for STI co-infections and cancer disease stage.
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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 | 0.045 | 0.159 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.019 |
| Bibliometrics | 0.029 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".