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Record W1778907140 · doi:10.1002/ijc.29459

Low ultraviolet-B exposure may explain some of the link between night shift work and increased risk of prostate cancer

2015· letter· en· W1778907140 on OpenAlexaboutno aff
William B. Grant

Bibliographic record

VenueInternational Journal of Cancer · 2015
Typeletter
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsProstate cancerMedicineVitamin D and neurologyNational Health and Nutrition Examination SurveyCancerSkin cancerIncidence (geometry)PhysiologySunlightOdds ratioDemographyEnvironmental healthGynecologyOncologyInternal medicinePopulation

Abstract

fetched live from OpenAlex

The paper by Papantoniou et al. reported that night shift work was associated with prostate cancer risk, with higher odds ratios for longer duration of exposure and for higher risk tumors.1 The primary mechanisms proposed to explain the finding were lower production of melatonin and circadian rhythm disruption. The authors reported lower sun exposure and vitamin D deficiency did not explain the findings. However, their analysis of the role of vitamin D in explaining the associations was based on past sun exposure, which is a poor index of vitamin D production since vitamin D cannot be produced from sun exposure in Spain for the darkest four-to-six months of the year or in early morning or late afternoon.2 Thus, without more information about sun exposure times, use of sunscreen, clothing worn and/or 25-hydroxyvitamin D [25(OH)D] concentrations, there is not enough information in this study to evaluate the role of UVB and vitamin D in the risk of prostate cancer. There is a large body of research finding that solar UVB and vitamin D reduce the risk of prostate cancer. Geographical ecological studies have found significant inverse correlations between indices of solar UVB doses and prostate cancer incidence and/or mortality rates in Australia, Nordic countries and the United States,3 and the mechanisms whereby vitamin D reduces risk of prostate cancer are well known.3 A study based on data from the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study found significant inverse associations “for men born in a region of high solar radiation (relative risk, 0.49, 95% confidence interval, 0.27–0.90 for high versus low solar radiation), with a slightly greater reduction for fatal than for nonfatal prostate cancer. Frequent recreational sun exposure in adulthood was associated with a significantly reduced risk of fatal prostate cancer only (relative risk, 0.47; 95% confidence interval, 0.23–0.99).”4 A vitamin D trial in which men with low grade prostate cancer were given 4,000 IU/d vitamin D3 for a year found “24 of 44 subjects (55%) showed a decrease in the number of positive cores or decrease in Gleason score; five subjects (11%) showed no change; 15 subjects (34%) showed an increase in the number of positive cores or Gleason score.”5 In comparison with historical control, there was a significant difference in the number of positive cores (decreased by about one in the trial vs. increased by about one in the controls). Lower 25(OH)D concentrations have been found more strongly correlated with aggressive prostate cancer than non-aggressive cancer,6 which supports the finding in Ref. 1 that risk from night shift work was higher for high risk tumors. A study of night work by males in Canada found an increased risk of many types of cancer including prostate cancer.7 In a letter to the editor, it was pointed out that most of the cancers with increased risk have been found to have risk inversely correlated with solar UVB doses in several ecological studies.8 In further support, it was noted that among nurses in the United States, night shift work was associated with reduced risk of melanoma and non-melanoma skin cancer, and that solar ultraviolet exposure is the greatest risk factor for these cancers.9 Thus, night shift workers should be advised that they should keep their 25(OH)D concentrations above 75–100 nmol/L through whatever combination of solar or artificial UVB exposure, diet and supplements works best for them. Doing so would also help them reduce risk of many other types of disease.10

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.029
GPT teacher head0.312
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreCommentary

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".

Quick stats

Citations4
Published2015
Admission routes1
Has abstractyes

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