The Relationship between Selenium and Lung Cancer: An Updated Systematic Review and Meta-Analysis

作者
Seyed Saman Talebi,Gholamreza Badfar,Masoumeh Shohani,Ali Soleymani,Milad Azami
出处
期刊:International journal of cancer management [Kowsar Medical Institute]
卷期号:11 (6) 被引量:5
标识
DOI:10.5812/ijcm.8370
摘要

Context: Many studies have reported contradictory results about the relationship between selenium levels and the risk of lung cancer. Objectives: This study was performed with the aim of evaluating the relationship between selenium and lung cancer. Methods: The present systematic review and meta-analysis was carried out according to preferred reporting items for systematic reviews and metaanalyses (PRISMA) guidelines. Using MeSH keywords, two reviewers independently searched international databases including PubMed, Science Direct, Cochrane, EMBASE, Web of Science, CINAHL, Scopus, and Google Scholar. The data were combined, using comprehensive Meta-Analysis Software Version 2 based on the random effects model. The tests were considered significant at P < 0.05. Results: In 15 high-quality studies including 13 case-control and 2 cohort studies, 84 199 subjects (2 434 cases and 81 765 controls) were studied. The odds ratio (OR) of lung cancer in the highest quintile of selenium exposure compared to the lowest quintile was 0.55 (95% CI: 0.35 to 0.86, P < 0.01). The results of the standardized mean difference between serum selenium concentrations in lung cancer and healthy groups in 11 studies (1446 cases and 77917 controls) was - 0.32 μg/L (95% CI: -0.53 to -0.11, P = 0.003). This value for toenails selenium in 3 studies (620 cases and 2 709 controls) was - 0.13 μg/g (95% CI: -0.22 to -0.038, P = 0.006). In subgroup analysis, it was determined that gender (P = 0.28), type of studies (P = 0.70), and measurement of selenium samples (P = 0.46) were not influencing factors. Conclusions: The results of the study indicated the preventive role of increased selenium levels in the incidence of lung cancer. Moreover, the selenium could be used as a predictive variable.

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