Shift work and risk of skin cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
Shift work with circadian disruption has been considered as a carcinogenic risk factor for skin cancer. The few prior studies that investigated the association between shift work and skin cancer have inconclusive results. Our main objective was to evaluate the associations between shift work and the risks of different types of skin cancer. We systematically searched PubMed, Web of Science, Cochrane Library, EMBASE and Science Direct until October 2018 for studies that included a relationship between shift work and skin cancer. Our search yielded 193 articles and 9 studies met the criteria for our review. The included studies involved 3,579,147 participants and 17,308 skin cancer cases. Overall, ever shift work, was associated with increased risk of melanoma (RR = 1.10, 95% CI = 1.05-1.16) and a significant decrease in the risk of BCC (RR = 0.90, 95% CI = 0.88-0.93). No association between shift work and the risk of SCC was detected. Interestingly, our dose response analysis demonstrated that the risk of melanoma cumulatively increases by 2% for every year of shift work (RR = 1.02; 95% CI = 1.00-1.03). In conclusion, shift work is associated with increased risk of melanoma and deceased risk of BCC. Further studies are needed to confirm our findings and to elucidate the related potential biological mechanisms.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.020 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".