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)

Assi, Nada; Moskal, Aurelie; Slimani, Nadia; Viallon, Vivian; Chajès, Véronique; Freisling, Heinz; Monni, Stefano; Knüppel, Sven; Förster, Jana; Weiderpass, Elisabete; Luján Barroso, Leila; Amiano, Pilar; Ardanaz, Eva; Molina Montes, Esther; Salmerón, Diego; Quirós, José Ramón; Olsen, Anja; Tjønneland, Anne; Dahm, Christina C.; Overvad, Kim; Dossus, Laure; Fournier, Agnès; Baglietto, Laura; Fortner, Renée T.; Kaaks, Rudolf; Trichopoulou, Antonia; Bamia, Christina; Orfanos, Philippos; Santucci de Magistris, Maria; Masala, Giovanna; Agnoli, Claudia; Ricceri, Fulvio; Tumino, Rosario; Bueno de Mesquita, H. Bas; Bakker, Marije F.; Peeters, Petra H. M.; Skeie, Guri; Braaten, Tonje; Winkvist, Anna; Johansson, Ingegerd

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)

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) an...

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Autores:	Assi, Nada, Moskal, Aurelie, Slimani, Nadia, Viallon, Vivian, Chajès, Véronique, Freisling, Heinz, Monni, Stefano, Knüppel, Sven, Förster, Jana, Weiderpass, Elisabete, Luján Barroso, Leila, Amiano, Pilar, Ardanaz, Eva, Molina Montes, Esther, Salmerón, Diego, Quirós, José Ramón, Olsen, Anja, Tjønneland, Anne, Dahm, Christina C., Overvad, Kim, Dossus, Laure, Fournier, Agnès, Baglietto, Laura, Fortner, Renée T., Kaaks, Rudolf, Trichopoulou, Antonia, Bamia, Christina, Orfanos, Philippos, Santucci de Magistris, Maria, Masala, Giovanna, Agnoli, Claudia, Ricceri, Fulvio, Tumino, Rosario, Bueno de Mesquita, H. Bas, Bakker, Marije F., Peeters, Petra H. M., Skeie, Guri, Braaten, Tonje, Winkvist, Anna, Johansson, Ingegerd
Tipo de recurso:	artículo
Estado:	Versión publicada
Fecha de publicación:	2016
País:	España
Institución:	Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:	Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:	oai:recercat.cat:2445/160098
Acceso en línea:	https://hdl.handle.net/2445/160098
Access Level:	acceso abierto
Palabra clave:	Nutrició Càncer Nutrition Cancer

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spelling	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)Assi, NadaMoskal, AurelieSlimani, NadiaViallon, VivianChajès, VéroniqueFreisling, HeinzMonni, StefanoKnüppel, SvenFörster, JanaWeiderpass, ElisabeteLuján Barroso, LeilaAmiano, PilarArdanaz, EvaMolina Montes, EstherSalmerón, DiegoQuirós, José RamónOlsen, AnjaTjønneland, AnneDahm, Christina C.Overvad, KimDossus, LaureFournier, AgnèsBaglietto, LauraFortner, Renée T.Kaaks, RudolfTrichopoulou, AntoniaBamia, ChristinaOrfanos, PhilipposSantucci de Magistris, MariaMasala, GiovannaAgnoli, ClaudiaRicceri, FulvioTumino, RosarioBueno de Mesquita, H. BasBakker, Marije F.Peeters, Petra H. M.Skeie, GuriBraaten, TonjeWinkvist, AnnaJohansson, IngegerdNutricióCàncerNutritionCancerObjective: 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.Cambridge University Press2020202020162020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion13 p.application/pdfhttps://hdl.handle.net/2445/160098Articles publicats en revistes (Infermeria de Salut Pública, Salut mental i Maternoinfantil)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1017/S1368980015000294Public Health Nutrition, 2016, vol. 19, num. 2, p. 242-254https://doi.org/10.1017/S1368980015000294info:eu-repo/grantAgreement/EC/FP7/232997(c) Assi, Nada et al., 2016info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1600982026-05-29T05:05:01Z
dc.title.none.fl_str_mv	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)
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)
spellingShingle	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) Assi, Nada Nutrició Càncer Nutrition Cancer
title_short	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)
title_full	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)
title_fullStr	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)
title_full_unstemmed	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)
title_sort	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)
dc.creator.none.fl_str_mv	Assi, Nada Moskal, Aurelie Slimani, Nadia Viallon, Vivian Chajès, Véronique Freisling, Heinz Monni, Stefano Knüppel, Sven Förster, Jana Weiderpass, Elisabete Luján Barroso, Leila Amiano, Pilar Ardanaz, Eva Molina Montes, Esther Salmerón, Diego Quirós, José Ramón Olsen, Anja Tjønneland, Anne Dahm, Christina C. Overvad, Kim Dossus, Laure Fournier, Agnès Baglietto, Laura Fortner, Renée T. Kaaks, Rudolf Trichopoulou, Antonia Bamia, Christina Orfanos, Philippos Santucci de Magistris, Maria Masala, Giovanna Agnoli, Claudia Ricceri, Fulvio Tumino, Rosario Bueno de Mesquita, H. Bas Bakker, Marije F. Peeters, Petra H. M. Skeie, Guri Braaten, Tonje Winkvist, Anna Johansson, Ingegerd
author	Assi, Nada
author_facet	Assi, Nada Moskal, Aurelie Slimani, Nadia Viallon, Vivian Chajès, Véronique Freisling, Heinz Monni, Stefano Knüppel, Sven Förster, Jana Weiderpass, Elisabete Luján Barroso, Leila Amiano, Pilar Ardanaz, Eva Molina Montes, Esther Salmerón, Diego Quirós, José Ramón Olsen, Anja Tjønneland, Anne Dahm, Christina C. Overvad, Kim Dossus, Laure Fournier, Agnès Baglietto, Laura Fortner, Renée T. Kaaks, Rudolf Trichopoulou, Antonia Bamia, Christina Orfanos, Philippos Santucci de Magistris, Maria Masala, Giovanna Agnoli, Claudia Ricceri, Fulvio Tumino, Rosario Bueno de Mesquita, H. Bas Bakker, Marije F. Peeters, Petra H. M. Skeie, Guri Braaten, Tonje Winkvist, Anna Johansson, Ingegerd
author_role	author
author2	Moskal, Aurelie Slimani, Nadia Viallon, Vivian Chajès, Véronique Freisling, Heinz Monni, Stefano Knüppel, Sven Förster, Jana Weiderpass, Elisabete Luján Barroso, Leila Amiano, Pilar Ardanaz, Eva Molina Montes, Esther Salmerón, Diego Quirós, José Ramón Olsen, Anja Tjønneland, Anne Dahm, Christina C. Overvad, Kim Dossus, Laure Fournier, Agnès Baglietto, Laura Fortner, Renée T. Kaaks, Rudolf Trichopoulou, Antonia Bamia, Christina Orfanos, Philippos Santucci de Magistris, Maria Masala, Giovanna Agnoli, Claudia Ricceri, Fulvio Tumino, Rosario Bueno de Mesquita, H. Bas Bakker, Marije F. Peeters, Petra H. M. Skeie, Guri Braaten, Tonje Winkvist, Anna Johansson, Ingegerd
author2_role	author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author
dc.subject.none.fl_str_mv	Nutrició Càncer Nutrition Cancer
topic	Nutrició Càncer Nutrition Cancer
description	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.
publishDate	2016
dc.date.none.fl_str_mv	2016 2020 2020 2020
dc.type.none.fl_str_mv	info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion
format	article
status_str	publishedVersion
dc.identifier.none.fl_str_mv	https://hdl.handle.net/2445/160098
url	https://hdl.handle.net/2445/160098
dc.language.none.fl_str_mv	Inglés
language_invalid_str_mv	Inglés
dc.relation.none.fl_str_mv	Reproducció del document publicat a: https://doi.org/10.1017/S1368980015000294 Public Health Nutrition, 2016, vol. 19, num. 2, p. 242-254 https://doi.org/10.1017/S1368980015000294 info:eu-repo/grantAgreement/EC/FP7/232997
dc.rights.none.fl_str_mv	(c) Assi, Nada et al., 2016 info:eu-repo/semantics/openAccess
rights_invalid_str_mv	(c) Assi, Nada et al., 2016
eu_rights_str_mv	openAccess
dc.format.none.fl_str_mv	13 p. application/pdf
dc.publisher.none.fl_str_mv	Cambridge University Press
publisher.none.fl_str_mv	Cambridge University Press
dc.source.none.fl_str_mv	Articles publicats en revistes (Infermeria de Salut Pública, Salut mental i Maternoinfantil) reponame:Recercat. Dipósit de la Recerca de Catalunya instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str	Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str	Recercat. Dipósit de la Recerca de Catalunya
collection	Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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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)

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