Incidence and Mortality of Prostate Cancer in Commercial Airline Cockpit Crew: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Commercial airline cockpit crew (CCC) are potentially exposed to occupational risk factors that may have detrimental health effects. However, available literature on prostate cancer (PCa) as a health outcome is conflicted. Therefore, this review of cohort studies aims to evaluate the incidence of and mortality from PCa in CCC based on studies published to date. PubMed, Medline, EMBASE and SCOPUS were searched from 1946 to April 2021. Cohort studies reporting standardized incidence ratios (SIR) and/or standardized mortality ratios (SMR) of PCa in CCC were included. Military, cabin crew and service personnel data were excluded. Independent data extraction was conducted, and study quality assessed. Standardized ratios were pooled using a fixed effects model and expressed with 95% confidence intervals. 75 studies were assessed for eligibility from which 6 involving 129 374 licensed CCC were included in the final analysis: Two reported incidence only, 1 incidence and mortality and 3 reported mortalities only. The pooled SIR for PCa in CCC was 1.41 (95% CI 1.17 to 1.71) with moderate heterogeneity (I2 = 53%) however, the pooled SMR was not statistically significant (1.08; 95% CI 0.94 to 1.24) also with moderate heterogeneity (I2 = 70%). The available evidence shows that CCC are at a higher risk of developing PCa but there is no evidence to suggest a similarly higher risk of death from the disease. The effect of early detection through PSA testing in this cohort is unclear. Occupational exposure to radiation and sleep disturbance may play a role, but clear evidence of additional risk is lacking. Our review indicates that most evidence is dated and to confidently assess contemporary health outcomes of CCC, further research is required.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".