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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)

Permanent link
https://hdl.handle.net/10037/10467
DOI
https://doi.org/10.1017/S1368980015000294
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Date
2015-02-23
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Assi, Nada; Moskal, Aurelie; Slimani, Nadia; Viallon, Vivian; Chajes, Veronique; Freisling, Heinz; Monni, Stefano; Knueppel, Sven; Förster, Jana; Weiderpass, Elisabete; Lujan-Barroso, Leila; Amiano, Pilar; Ardanaz, Eva; Molina-Montes, Esther; Salmeron, Diego; Quiros, Jose Ramon; Olsen, Anja; Tjonneland, Anne; Dahm, Christina C; Overvad, Kim; Dossus, Laure; Fournier, Agnes; Baglietto, Laura; Fortner, Renee Turzanski; Kaaks, Rudolf; Trichopoulou, Antonia; Bamia, Christina; Orfanos, Philippos; de Magistris, Maria Santucci; Masala, Giovanna; Agnoli, Claudia; Ricceri, Fulvio; Tumino, Rosario; Bueno De Mesquita, H Bas; Bakker, Marije F; Peeters, Petra HM; Skeie, Guri; Braaten, Tonje; Winkvist, Anna; Johansson, Ingegerd; Khaw, Kay-Tee; Wareham, Nicholas J; Key, Tim; Travis, Ruth; Schmidt, Julie A; Merritt, Melissa A; Riboli, Elio; Romieu, Isabelle; Ferrari, Pietro
Abstract
Objective: 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.
Design: 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.
Setting: The European Prospective Investigation into Cancer and Nutrition (EPIC).
Subjects: Women (n 334 850) from the EPIC study.
Results: 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, Ptrend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, Ptrend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, Ptrend<0·01).
Conclusions: 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.
Description
Published version. Source at https://doi.org/10.1017/S1368980015000294
Publisher
Cambridge University Press
Citation
Assi, N. 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 Nutrition. 2016;19(2):242-254
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