作者
Facundo Vitelli-Storelli, Marta Rossi, Claudio Pelucchi, Matteo Rota, Domenico Palli, Monica Ferraroni, Nuno Lunet, Samantha Morais, Lizbeth López-Carrillo, David Georgievich Zaridze, Dmitry Maximovich, Maria Rubin Garcia, Gemma Castano-Vinyals, Nuria Aragonés, Manuela Garcia de la Hera, Raul Ulises Hernandez-Ramirez, Eva Negri, Rossella Bonzi, Mary H Ward, Areti Lagiou, Pagona Lagiou, Malaquias Lopez-Cervantes, Paolo Boffetta, M Constanza Camargo, Maria Paula Curado, Zuo-Feng Zhang, Jesus Vioque, Carlo La Vecchia, Vicente Martin Sanchez
发表日期
2020/10/20
期刊
Cancers
卷号
12
期号
10
页码范围
3064
出版商
MDPI
简介
Simple Summary
Gastric cancer (GC) has the fifth highest incidence of any cancer type worldwide and the third highest mortality rate, so its prevention is very important. Among dietary factors, the consumption of fruit and vegetables has been inversely related to GC risk. Phenolic compounds may exert a favorable effect on the risk of several cancer types, including gastric cancer. However, selected polyphenol classes have not been adequately investigated in relation to GC. There is, however, no comprehensive analysis of polyphenols and GC risk methods to date. In order to provide a detailed evaluation of the relationship between dietary intake of polyphenols and GC risk, we analyzed data from the Stomach cancer Pooling (StoP) Project consortium.
Abstract
Phenolic compounds may exert a favorable effect on the risk of several cancer types, including gastric cancer (GC). However, selected polyphenol classes have not been adequately investigated in relation to GC. The aim of this study is to evaluate the association between the intake of polyphenols in relation to GC risk. We used data from the Stomach cancer Pooling (StoP) Project, including 10 studies from six countries (3471 GC cases and 8344 controls). We carried out an individual participant data pooled analysis using a two-stage approach. The summary odds ratios (ORs) of GC for each compound, and the corresponding 95% confidence intervals (95% CI), were computed by pooling study specific ORs obtained through multivariate logistic regression, using random effect models. Inverse associations with GC emerged for total polyphenols (OR = 0.67 …
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