Association of cigarette smoking habits with the risk of prostate cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Association of cigarette smoking habits with the risk of prostate cancer is still a matter of debate. This systematic review and meta-analysis aimed to assess the association between cigarette smoking and prostate cancer risk. Methods We conducted a systematic search on PubMed, Embase, Cochrane Library, and Web of Science without language or time restrictions on June 11, 2022. Literature search and study screening were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Prospective cohort studies that assessed the association between cigarette smoking habits and the risk of prostate cancer were included. Quality assessment was conducted using the Newcastle–Ottawa Scale. We used random-effects models to obtain pooled estimates and the corresponding 95% confidence intervals. Results A total of 7296 publications were screened, of which 44 cohort studies were identified for qualitative analysis; 39 articles comprising 3 296 398 participants and 130 924 cases were selected for further meta-analysis. Current smoking had a significantly reduced risk of prostate cancer (RR, 0.74; 95% CI, 0.68–0.80; P < 0.001), especially in studies completed in the prostate-specific antigen screening era. Compared to former smokers, current smokers had a significant lower risk of PCa (RR, 0.70; 95% CI, 0.65–0.75; P < 0.001). Ever smoking showed no association with prostate cancer risk in overall analyses (RR, 0.96; 95% CI, 0.93–1.00; P = 0.074), but an increased risk of prostate cancer in the pre-prostate-specific antigen screening era (RR, 1.05; 95% CI, 1.00–1.10; P = 0.046) and a lower risk of prostate cancer in the prostate-specific antigen screening era (RR, 0.95; 95% CI, 0.91–0.99; P = 0.011) were observed. Former smoking did not show any association with the risk of prostate cancer. Conclusions The findings suggest that the lower risk of prostate cancer in smokers can probably be attributed to their poor adherence to cancer screening and the occurrence of deadly smoking-related diseases, and we should take measures to help smokers to be more compliant with early cancer screening and to quit smoking. Trial registration This study was registered on PROSPERO (CRD42022326464).
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".