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Diet and ovarian cancer risk: An umbrella review of systematic reviews and meta-analyses of cohort studies 飲食和卵巢癌風險：對系統(tǒng)性綜述和隊列研究薈萃分析的傘形評價 10.1016/j.clnu.2020.11.032 11-27, Review Abstract & Authors:展開 Abstract:收起
Background & aims: Diet may play an important role in the etiology of ovarian cancer (OC). We aimed to evaluate the strength and credibility of evidence pertaining to dietary risk factors for OC.
Methods: We comprehensively searched PubMed, Web of Science, Cochrane, CINAHL, JBI Database of Systematic Reviews and Implementation Reports, PROSPERO and EMBASE databases to identify related systematic reviews and meta-analyses of prospective cohort studies. This study had been registered at PROSPERO. The registration number is CRD42020187651. For each association, we estimated the summary effect size using fixed and random effects models, the 95% confidence interval and the 95% prediction interval. We assessed heterogeneity, evidence of small-study effects, and excess significance bias.
Results: A total of 22 systematic reviews and meta-analyses were included in the present study. These previous reports evaluated 184 individual studies, which proposed a total of 36 associations between dietary factors and OC risk. Out of the 36 associations, there were no strong, highly suggestive and suggestive evidence, only four (black tea, skim/low-fat milk, lactose, and calcium) were determined to be supported by weak evidence. OC risk was inversely associated with intake of black tea or calcium, and positively associated with intake of skim/low-fat milk or lactose.
Conclusions: Our studies revealed that four associations between OC risk and dietary factors (black tea, skim/low-fat milk, lactose, and calcium) were supported by weak evidence. The remaining 32 associations were not confirmed. Additional studies are needed to carefully evaluate the relationship between dietary factors and OC risk.
First Authors:
Hui Sun Correspondence Authors:
Yu-Hong Zhao,Qi-Jun Wu All Authors:
Hui Sun,Ting-Ting Gong,Xianwei Yang,Zhao-Yan Wen,Long-Gang Zhao,Yu-Hong Zhao,Qi-Jun Wu
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