From the aDepartment of Computer Science, Princeton University, Princeton, NJbDivision of Public Health, Department of Family & Preventive Medicine, University of Utah School of Medicine, Salt Lake City, UTcDepartment of Medicine, University of Udine, Udine, ItalydEpidemiology and Biostatistics Unit, CRO Aviano National Cancer Institute, IRCCS, Aviano, ItalyeUniversity of North Carolina School of Public Health, Chapel Hill, NCfDepartment of Otolaryngology/Head and Neck Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NCgInstitute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital (CHUV), Lausanne, SwitzerlandhDepartment of Epidemiology, UCLA School of Public Health, Los Angeles, CAiDepartments of Epidemiology and Environmental Health Sciences, School of Public Health and Comprehensive Cancer Center, University of Michigan, Ann Arbor, MIjDepartment of Otorhinolaryngology, School of Medicine and Surgery, University of Milano - Bicocca, Monza, ItalykDepartment of Epidemiology and Pathology and Laboratory Medicine, Brown University, Providence, RIlDepartment of Environmental Health, Boston University School of Public Health, Boston, MAmDepartment of Otolaryngology, New York Eye and Ear Infirmary, New York, NYnMedical Informatics Center, Peking University, Peking, ChinaoThe Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NYpInstitute of Population Health Sciences, National Health Research Institutes, Miaoli, TaiwanqDivision of Public Health, Department of Family & Preventive Medicine and Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UTrBranch of Medical Statistics, Biometry and Epidemiology “G. A. Maccacaro,” Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milano, ItalysDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MAtDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA.
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Background:A few papers have considered reproducibility of a posteriori dietary patterns across populations, as well as pattern associations with head and neck cancer risk when multiple populations are available.Methods:We used individual-level pooled data from seven case–control studies (3844 cases; 6824 controls) participating in the International Head and Neck Cancer Epidemiology consortium. We simultaneously derived shared and study-specific a posteriori patterns with a novel approach called multi-study factor analysis applied to 23 nutrients. We derived odds ratios (ORs) and 95% confidence intervals (CIs) for cancers of the oral cavity and pharynx combined, and larynx, from logistic regression models.Results:We identified three shared patterns that were reproducible across studies (75% variance explained): the Antioxidant vitamins and fiber (OR = 0.57, 95% CI = 0.41, 0.78, highest versus lowest score quintile) and the Fats (OR = 0.80, 95% CI = 0.67, 0.95) patterns were inversely associated with oral and pharyngeal cancer risk. The Animal products and cereals (OR = 1.5, 95% CI = 1.1, 2.1) and the Fats (OR = 1.8, 95% CI = 1.4, 2.3) patterns were positively associated with laryngeal cancer risk, whereas a linear inverse trend in laryngeal cancer risk was evident for the Antioxidant vitamins and fiber pattern. We also identified four additional study-specific patterns, one for each of the four US studies examined. We named them all as Dairy products and breakfast cereals, and two were associated with oral and pharyngeal cancer risk.Conclusion:Multi-study factor analysis provides insight into pattern reproducibility and supports previous evidence on cross-country reproducibility of dietary patterns and on their association with head and neck cancer risk. See video abstract at, http://links.lww.com/EDE/B430.