RT Journal Article
T1 A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).
A1 Assi, Nada
A1 Moskal, Aurelie
A1 Slimani, Nadia
A1 Viallon, Vivian
A1 Chajes, Veronique
A1 Freisling, Heinz
A1 Monni, Stefano
A1 Knueppel, Sven
A1 Förster, Jana
A1 Weiderpass, Elisabete
A1 Lujan-Barroso, Leila
A1 Amiano, Pilar
A1 Ardanaz, Eva
A1 Molina-Montes, Esther
A1 Salmerón, Diego
A1 Quirós, José Ramón
A1 Olsen, Anja
A1 Tjønneland, Anne
A1 Dahm, Christina C
A1 Overvad, Kim
A1 Dossus, Laure
A1 Fournier, Agnès
A1 Baglietto, Laura
A1 Fortner, Renee Turzanski
A1 Kaaks, Rudolf
A1 Trichopoulou, Antonia
A1 Bamia, Christina
A1 Orfanos, Philippos
A1 De Magistris, Maria Santucci
A1 Masala, Giovanna
A1 Agnoli, Claudia
A1 Ricceri, Fulvio
A1 Tumino, Rosario
A1 Bueno de Mesquita, H Bas
A1 Bakker, Marije F
A1 Peeters, Petra Hm
A1 Skeie, Guri
A1 Braaten, Tonje
A1 Winkvist, Anna
A1 Johansson, Ingegerd
A1 Khaw, Kay-Tee
A1 Wareham, Nicholas J
A1 Key, Tim
A1 Travis, Ruth
A1 Schmidt, Julie A
A1 Merritt, Melissa A
A1 Riboli, Elio
A1 Romieu, Isabelle
A1 Ferrari, Pietro
K1 Breast cancer
K1 European Prospective Investigationinto Cancer and Nutrition
K1 Nutrient patterns
K1 Principal component analysis
K1 Treelet transform
AB Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology. Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison. The European Prospective Investigation into Cancer and Nutrition (EPIC). Women (n 334 850) from the EPIC study. The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, P trend TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.
PB Cambridge University Press
YR 2015
FD 2015-02-23
LK http://hdl.handle.net/10668/9661
UL http://hdl.handle.net/10668/9661
LA en
NO Assi N, Moskal A, Slimani N, Viallon V, Chajes V, Freisling H, et al. A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr. 2016 Feb;19(2):242-54.
DS RISalud
RD Apr 8, 2025