Nightshift work and risk of breast and prostate cancer: a systematic review and meta-analysis, 2012-2023
Bibliographic record
Abstract
BACKGROUND: The International Agency for Research on Cancer classifies night shift work as Group 2A, a probable human carcinogen. This study updates the evidence on the association between night shift work and the risk of breast and prostate cancer. METHODS: Searches were conducted in PubMed and Web of Science. Case-control and cohort studies were included if they assessed night work as a risk factor for breast or prostate cancer, had =100 participants, provided full text in English or Spanish, scored =6 on the Newcastle-Ottawa Scale, and reported relative risks or odds ratio with 95% confidence interval. Heterogeneity and study quality were evaluated. Data synthesis followed PRISMA guidelines. RESULTS: Twenty-one studies including 586,890 participants were analysed. For breast cancer, significant association were found only in cohort studies, both overall (RR=0.82; 95%CI: 0.67-0.99; I2=91%) and for <10 years of night work (RR=0.75; 95% CI: 0.68-0.82; I2=0%). Average study quality was acceptable (score 7), although heterogeneity was substantial. For prostate cancer, case-control studies reported an OR of 1.14 (95%CI; 1.02-1.27; I2=25%). For exposures =10 years, both RR (2.20; 95%CI: 1.35-3.59) and OR (1.16; 95%CI: 1.03-1.30) were significant. Overall quality was moderate (score 6) with low heterogeneity (25%). CONCLUSIONS: Weak associations between night shift work and prostate cancer are observed in case-control studies and among individuals with =10 years of exposure, but no consistent association was found for breast cancer. These findings remain inconclusive and highlight the need for further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.035 |
| 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".