Association between vasectomy and risk of testicular cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: A number of researchers have reported that vasectomy is a risk factor for testicular cancer. However, this conclusion is inconsistent with a number of other published articles. Hence, we conducted this meta-analysis to assess whether vasectomy increases the risk of testicular cancer. MATERIALS AND METHODS: We identified all related studies by searching the PubMed, Embase, and Cochrane Library database from January 01, 1980 to June 01, 2017. The Newcastle-Ottawa Scale (NOS) checklist was used to assess all included non-randomized studies. Summarized odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the difference in outcomes between case and control groups. Subgroup analyses were performed according to the study design and country. RESULTS: A total of eight studies (2176 testicular cancer patients) were included in this systematic review and meta-analysis. Six articles were case-control studies, and two were cohort studies. The pooled estimate of the OR was 1.10 (95% CI: 0.93-1.30) based on the eight studies in a fixed effects model. Two subgroup analyses were performed according to the study design and country. The results were consistent with the overall findings. Publication bias was detected by Begg's test and Egger's test and p values > 0.05, respectively. CONCLUSIONS: Our meta-analysis suggested that there was no association between vasectomy and the development of testicular cancer. More high-quality studies are warranted to further explore the association between vasectomy and risk of testicular cancer.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.047 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".