Risk of cancer among individuals with a history of bacterial sexually transmitted infections: A population‐based study in Alberta, Canada
Bibliographic record
Abstract
We investigated cancer risk among individuals with a prior bacterial sexually transmitted infection (STI) diagnosis using a retrospective cohort study of all Albertan residents diagnosed with chlamydia, gonorrhea, or syphilis during 2000-2014, that was then linked to the Alberta Cancer Registry. Follow-up started 5 years from their first bacterial STI diagnosis and continued until the first instance of a cancer diagnosis, death, or the study end date (December 31, 2019). Internal comparisons between the bacterial STI groups were undertaken using adjusted hazard ratios, while sex-specific standardized incidence ratios (SIRs) were calculated to compare cancer risk with the Alberta general population. The likelihood of developing cancer was largely comparable within the bacterial STI cohort, though head/neck cancer was more common after only gonorrhea exposure, and lung cancer was more common after only syphilis exposure. When compared with the general population, statistically significant SIRs were observed among females for cervical cancer (SIR = 1.9, 95%CI = 1.5, 2.3) and thyroid cancer (SIR = 0.8, 95%CI = 0.6, 0.9); females exposed to chlamydia with other STIs, or gonorrhea with other STIs, were also 3.2- and 2.9-times more likely to develop colon cancer, respectively. In males, statistically significantly associations were identified for cancer overall (SIR = 1.1, 95%CI = 1.0, 1.2) and Hodgkin lymphoma (SIR = 1.8, 95%CI = 1.0, 2.9); males exposed to chlamydia only were also 1.5- and 1.6-times more likely to develop prostate and testicular cancer, respectively, while males exposed to only syphilis were 2.4-times more likely to develop lung cancer. Our findings are consistent with common bacterial STIs being correlates of risk of certain cancers, although the possible etiologic mechanisms may be indirect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".