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000179587 1001_ $$00000-0002-1778-9998$$aKliemann, Nathalie$$b0
000179587 245__ $$aMetabolically-Defined Body Size Phenotypes and Risk of Endometrial Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).
000179587 260__ $$aPhiladelphia, Pa.$$bAACR$$c2022
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000179587 500__ $$a2022 Jul 1;31(7):1359-1367
000179587 520__ $$aObesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known.The association of metabolically-defined body size phenotypes with endometrial cancer risk was investigated in a nested case-control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH; <1st tertile) and metabolically unhealthy (MU; >=1st tertile) status among the control participants. These metabolic health definitions were combined with normal weight (NW; Body Mass Index (BMI)<25kg/m2 or Waist Circumference (WC)<80cm or Waist-to-Hip Ratio (WHR)<0.8) and overweight (OW; BMI>=25kg/m2 or WC>=80cm or WHR>=0.8) status, generating four phenotype groups for each anthropometric measure: (1)MH/NW, (2)MH/OW (3)MU/NW and (4)MU/OW.In a multivariable-adjusted conditional logistic regression model, compared with MH/NW individuals, endometrial cancer risk was higher among those classified as MU/NW (OR/WC=1.48; 95%CI 1.05-2.10 and OR/WHR=1.68; 95%CI 1.21-2.35) and MU/OW (OR/BMI=2.38, 95%CI 1.73-3.27; OR/WC=2.69, 95%CI 1.92-3.77 and OR/WHR=1.83, 95%CI 1.32-2.54). MH/OW individuals were also at increased endometrial cancer risk compared to MH/NW individuals (OR/WC=1.94, 95%CI 1.24-3.04).Women with metabolic dysfunction appear to have higher risk of endometrial cancer regardless of their body size. However, overweight status raises endometrial cancer risk even among women with lower insulin levels, suggesting that obesity-related pathways are relevant for the development of this cancer beyond insulin.Classifying women by metabolic health may be of greater utility in identifying those at higher risk for endometrial cancer than anthropometry per se.
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000179587 7001_ $$00000-0003-4801-3401$$aOuld Ammar, Romain$$b1
000179587 7001_ $$00000-0003-3950-0929$$aBiessy, Carine$$b2
000179587 7001_ $$aGicquiau, Audrey$$b3
000179587 7001_ $$0P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4$$aKatzke, Verena$$b4$$udkfz
000179587 7001_ $$0P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aKaaks, Rudolf$$b5$$udkfz
000179587 7001_ $$aTjoenneland, Anne$$b6
000179587 7001_ $$00000-0003-4788-503X$$aOlsen, Anja$$b7
000179587 7001_ $$00000-0003-4817-0757$$aSánchez, Maria-Jose$$b8
000179587 7001_ $$aCrous-Bou, Marta$$b9
000179587 7001_ $$aPasanisi, Fabrizio$$b10
000179587 7001_ $$aTin Tin, Sandar$$b11
000179587 7001_ $$00000-0002-5652-356X$$aPerez-Cornago, Aurora$$b12
000179587 7001_ $$00000-0002-4533-1722$$aAune, Dagfinn$$b13
000179587 7001_ $$aChristakoudi, Sofia$$b14
000179587 7001_ $$00000-0001-6517-1300$$aHeath, Alicia K$$b15
000179587 7001_ $$aColorado-Yohar, Sandra M$$b16
000179587 7001_ $$00000-0002-5891-8426$$aGrioni, Sara$$b17
000179587 7001_ $$00000-0003-2476-4251$$aSkeie, Guri$$b18
000179587 7001_ $$00000-0002-1116-5199$$aSartor, Hanna$$b19
000179587 7001_ $$00000-0002-7865-4560$$aIdahl, Annika$$b20
000179587 7001_ $$aRylander, Charlotta$$b21
000179587 7001_ $$aM May, Anne$$b22
000179587 7001_ $$00000-0003-2237-0128$$aWeiderpass, Elisabete$$b23
000179587 7001_ $$00000-0001-8648-4998$$aFreisling, Heinz$$b24
000179587 7001_ $$00000-0001-6082-0447$$aPlaydon, Mary C$$b25
000179587 7001_ $$aRinaldi, Sabina$$b26
000179587 7001_ $$aMurphy, Neil$$b27
000179587 7001_ $$00000-0003-3838-855X$$aHuybrechts, Inge$$b28
000179587 7001_ $$00000-0003-2716-5748$$aDossus, Laure$$b29
000179587 7001_ $$00000-0001-5472-6761$$aGunter, Marc J$$b30
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