{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Assi N"],"funding":["Cancer Research UK","Medical Research Council","National Institute for Health Research (NIHR)","Wellcome Trust"],"pagination":["242-54"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10270861"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["19(2)"],"pubmed_abstract":["<h4>Objective</h4>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.<h4>Design</h4>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.<h4>Setting</h4>The European Prospective Investigation into Cancer and Nut"],"journal":["Public health nutrition"],"pubmed_title":["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)."],"pmcid":["PMC10270861"],"funding_grant_id":["MC_UU_12015/1","G1000143","NF-SI-0512-10135","G0401527","NF-SI-0512-10114","14136","16491","MC_U106179471"],"pubmed_authors":["Bueno de Mesquita HB","Peeters PH","Salmeron D","Baglietto L","Freisling H","Knueppel S","Trichopoulou A","Tjonneland A","Weiderpass E","Schmidt JA","Ferrari P","Assi N","Tumino R","Orfanos P","Lujan-Barroso L","Travis R","Agnoli C","Winkvist A","Bamia C","Braaten T","Fortner RT","Merritt MA","Viallon V","Bakker MF","Dahm CC","Kaaks R","Skeie G","Khaw KT","Forster J","Chajes V","Fournier A","Molina-Montes E","Wareham NJ","De Magistris MS","Riboli E","Overvad K","Masala G","Key T","Ardanaz E","Slimani N","Quiros JR","Ricceri F","Monni S","Dossus L","Romieu I","Moskal A","Olsen A","Amiano P","Johansson I"],"additional_accession":[]},"is_claimable":false,"name":"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).","description":"<h4>Objective</h4>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.<h4>Design</h4>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.<h4>Setting</h4>The European Prospective Investigation into Cancer and Nut","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016 Feb","modification":"2025-04-22T18:47:38.317Z","creation":"2025-04-06T02:35:38.834Z"},"accession":"S-EPMC10270861","cross_references":{"pubmed":["25702596"],"doi":["10.1017/S1368980015000294","10.1017/s1368980015000294"]}}