Article open access publication

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, Cambridge University Press (CUP), ISSN 1368-9800

Volume 19, 2, 2016

DOI:10.1017/s1368980015000294, Dimensions: pub.1023103967, PMID: 25702596,



  1. (1) International Agency For Research On Cancer, grid.17703.32
  2. (2) Claude Bernard University Lyon 1, grid.7849.2
  3. (3) French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks, grid.249503.9
  4. (4) University of Lyon System, grid.25697.3f
  5. (5) German Cancer Research Center, grid.7497.d
  6. (6) German Institute of Human Nutrition, grid.418213.d
  7. (7) Cancer Registry of Norway, grid.418941.1
  8. (8) Folkhälsans Forskningscentrum, grid.428673.c
  9. (9) Karolinska Institute, grid.4714.6
  10. (10) The Arctic University of Norway, grid.10919.30
  11. (11) Unit of Nutrition, Environment and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
  12. (12) Public Health Division of Gipuzkoa, BioDonostia Research Institute, Health Department, San Sebastian, Spain
  13. (13) Institute of Health Carlos III, grid.413448.e
  14. (14) Instituto de Salud Pública de Navarra, grid.419126.9
  15. (15) Andalusian School of Public Health, grid.413740.5
  16. (16) Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain
  17. (17) University of Murcia, grid.10586.3a
  18. (18) Public Health Directorate, Asturias, Oviedo, Spain
  19. (19) Danish Cancer Society, grid.417390.8
  20. (20) Aarhus University, grid.7048.b, AU
  21. (21) Centre for research in epidemiology and population health, grid.463845.8
  22. (22) Institut Gustave Roussy, grid.14925.3b
  23. (23) University of Paris-Sud, grid.5842.b
  24. (24) Cancer Council Victoria, grid.3263.4
  25. (25) University of Melbourne, grid.1008.9
  26. (26) Academy of Athens, grid.417593.d
  27. (27) Hellenic Health Foundation, grid.424637.0
  28. (28) National and Kapodistrian University of Athens, grid.5216.0
  29. (29) Federico II University Hospital, grid.411293.c
  30. (30) Istituto per lo Studio e la Prevenzione Oncologica, grid.417623.5
  31. (31) Fondazione IRCCS Istituto Nazionale dei Tumori, grid.417893.0
  32. (32) University of Turin, grid.7605.4
  33. (33) Cancer Registry and Histopathology Unit, ‘Civile M.P. Arezzo’ Hospital, Ragusa, Italy
  34. (34) National Institute for Public Health and the Environment, grid.31147.30
  35. (35) University Medical Center Utrecht, grid.7692.a
  36. (36) Imperial College London, grid.7445.2
  37. (37) University of Gothenburg, grid.8761.8
  38. (38) Umeå University, grid.12650.30
  39. (39) University of Cambridge, grid.5335.0
  40. (40) University of Oxford, grid.4991.5


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, P trend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, P trend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, P trend<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.


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