Night-shift work and breast and prostate cancer risk: updating the evidence from epidemiological studies
Bibliographic record
Abstract
It has been hypothesized that circadian disruption is related to higher cancer risk. Since the International Agency for Research on Cancer classified shift work involving circadian disruption as probably carcinogenic to humans (Group 2A), multiple studies have been conducted to test this hypothesis. The aim of this systematic review was to summarize the findings and evaluate the quality of existing epidemiological studies (case-control and cohort studies) on the relationship between night-shift work and breast and prostate cancer risk. Thirty-three epidemiological studies investigating the relationship between night-shift work and breast (n = 26) or prostate (n = 8) cancer risk were included (one paper included both sites). The Newcastle-Ottawa Scale for the quality of non-randomized studies was used to assess the risk of bias of the publications. The studies included were heterogeneous regarding population (general population, nurses working in rotating shifts, and other) and measurement of exposure to night-shift work (ever vs. never exposure, short vs. long-term, rotating vs. permanent) and, thus, a diversity of outcomes were observed even within the same type of cancer. In summary, 62.5% works found some type of association between night-shift work and increased risk of cancer, for both breast and prostate. The risk of bias scored an average of 7.5 over 9 stars. Due to the limitations inherent in these studies, the evidence of a possible association between night-shift work and breast or prostate cancer risk remains uncertain and more studies providing greater control of exposure and confounding factors are required. Despite the lack of conclusive evidence, application of the precautionary principle seems advisable.
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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 | 0.074 | 0.221 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.019 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".