Literature DB >> 21697276

Metabolic syndrome and risks of colon and rectal cancer: the European prospective investigation into cancer and nutrition study.

Krasimira Aleksandrova1, Heiner Boeing, Mazda Jenab, H Bas Bueno-de-Mesquita, Eugene Jansen, Fränzel J B van Duijnhoven, Veronika Fedirko, Sabina Rinaldi, Isabelle Romieu, Elio Riboli, Dora Romaguera, Kim Overvad, Jane Nautrup Østergaard, Anja Olsen, Anne Tjønneland, Marie-Christine Boutron-Ruault, Françoise Clavel-Chapelon, Sophie Morois, Giovanna Masala, Claudia Agnoli, Salvatore Panico, Rosario Tumino, Paolo Vineis, Rudolf Kaaks, Annekatrin Lukanova, Antonia Trichopoulou, Androniki Naska, Christina Bamia, Petra H Peeters, Laudina Rodríguez, Genevieve Buckland, María-José Sánchez, Miren Dorronsoro, Jose-María Huerta, Aurelio Barricarte, Göran Hallmans, Richard Palmqvist, Kay-Tee Khaw, Nicholas Wareham, Naomi E Allen, Konstantinos K Tsilidis, Tobias Pischon.   

Abstract

Metabolic syndrome (MetS) is purportedly related to risk of developing colorectal cancer; however, the association of MetS, as defined according to recent international criteria, and colorectal cancer has not been yet evaluated. In particular, it remains unclear to what extent the MetS components individually account for such an association. We addressed these issues in a nested case-control study that included 1,093 incident cases matched (1:1) to controls by using incidence density sampling. Conditional logistic regression was used to estimate relative risks (RR) and 95% CIs. MetS was defined according to the criteria of the National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATPIII), the International Diabetes Federation (IDF), and the 2009 harmonized definition. Among individual components, abdominal obesity (RR = 1.51; 95% CI: 1.16-1.96) was associated with colon cancer, whereas abnormal glucose metabolism was associated with both colon (RR = 2.05; 95% CI: 1.57-2.68) and rectal cancer (RR = 2.07; 95% CI: 1.45-2.96). MetS, as defined by each of the definitions, was similarly associated with colon cancer (e.g., RR = 1.91; 95% CI: 1.47-2.42 for MetS by NCEP/ATPIII), whereas MetS by NCEP/ATPIII, but not IDF or harmonized definition, was associated with rectal cancer (RR = 1.45; 95% CI: 1.02-2.06). Overall, these associations were stronger in women than in men. However, the association between MetS and colorectal cancer was accounted for by abdominal obesity and abnormal glucose metabolism such that MetS did not provide risk information beyond these components (likelihood ratio test P = 0.10 for MetS by NCEP/ATPIII). These data suggest that simple assessment of abnormal glucose metabolism and/or abdominal obesity to identify individuals at colorectal cancer risk may have higher clinical utility than applying more complex MetS definitions.

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Year:  2011        PMID: 21697276     DOI: 10.1158/1940-6207.CAPR-11-0218

Source DB:  PubMed          Journal:  Cancer Prev Res (Phila)        ISSN: 1940-6215


  52 in total

1.  Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer.

Authors:  Baoku Quan; Xingsi Qi; Zhihui Yu; Yongshuai Jiang; Mingzhi Liao; Guangyu Wang; Rennan Feng; Liangcai Zhang; Zugen Chen; Qinghua Jiang; Guiyou Liu
Journal:  Mol Genet Genomics       Date:  2014-11-02       Impact factor: 3.291

2.  Specific features of colorectal cancer in patients with metabolic syndrome: a matched case-control analysis of 772 patients.

Authors:  Alban Zarzavadjian Le Bian; Christine Denet; Nicolas Tabchouri; Gianfranco Donatelli; Philippe Wind; Christophe Louvet; Mostefa Bennamoun; Christos Christidis; Thierry Perniceni; David Fuks; Brice Gayet
Journal:  Langenbecks Arch Surg       Date:  2018-04-27       Impact factor: 3.445

3.  Abdominal obesity, glucose intolerance and decreased high-density lipoprotein cholesterol as components of the metabolic syndrome are associated with the development of colorectal cancer.

Authors:  Yoon Jin Choi; Dong Ho Lee; Kyung-Do Han; Cheol Min Shin; Nayoung Kim
Journal:  Eur J Epidemiol       Date:  2018-09-08       Impact factor: 8.082

Review 4.  The association between metabolic syndrome and hepatocellular carcinoma: systemic review and meta-analysis.

Authors:  Raxitkumar Jinjuvadia; Suhag Patel; Suthat Liangpunsakul
Journal:  J Clin Gastroenterol       Date:  2014-02       Impact factor: 3.062

5.  In-Hospital Mortality and Post-Surgical Complications Among Cancer Patients with Metabolic Syndrome.

Authors:  Tomi Akinyemiju; Swati Sakhuja; Neomi Vin-Raviv
Journal:  Obes Surg       Date:  2018-03       Impact factor: 4.129

Review 6.  The role of FAK in tumor metabolism and therapy.

Authors:  Jianliang Zhang; Steven N Hochwald
Journal:  Pharmacol Ther       Date:  2013-12-09       Impact factor: 12.310

Review 7.  Specific metabolic biomarkers as risk and prognostic factors in colorectal cancer.

Authors:  Małgorzata Muc-Wierzgoń; Ewa Nowakowska-Zajdel; Sylwia Dzięgielewska-Gęsiak; Teresa Kokot; Katarzyna Klakla; Edyta Fatyga; Elżbieta Grochowska-Niedworok; Dariusz Waniczek; Janusz Wierzgoń
Journal:  World J Gastroenterol       Date:  2014-08-07       Impact factor: 5.742

Review 8.  Colorectal cancer association with metabolic syndrome and its components: a systematic review with meta-analysis.

Authors:  Katherine Esposito; Paolo Chiodini; Annalisa Capuano; Giuseppe Bellastella; Maria Ida Maiorino; Concetta Rafaniello; Demosthenes B Panagiotakos; Dario Giugliano
Journal:  Endocrine       Date:  2013-04-02       Impact factor: 3.633

9.  Visceral obesity and colorectal cancer: are we missing the boat with BMI?

Authors:  Aaron S Rickles; James C Iannuzzi; Oleg Mironov; Andrew-Paul Deeb; Abhiram Sharma; Fergal J Fleming; John R T Monson
Journal:  J Gastrointest Surg       Date:  2012-10-23       Impact factor: 3.452

Review 10.  The association between metabolic syndrome and colorectal neoplasm: systemic review and meta-analysis.

Authors:  Raxitkumar Jinjuvadia; Prateek Lohia; Chetna Jinjuvadia; Sergio Montoya; Suthat Liangpunsakul
Journal:  J Clin Gastroenterol       Date:  2013-01       Impact factor: 3.062

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