S Pirouzpanah1, F-A Taleban2, P Mehdipour3, M Atri4, A Hooshyareh-rad5, S Sabour6. 1. 1] Department of Community Nutrition, Faculty of Health and Nutrition, Tabriz University of Medical Sciences, Tabriz, Iran [2] Department of Clinical Nutrition & Dietetics, Faculty of Nutrition Sciences and Food Technology/National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. Department of Clinical Nutrition & Dietetics, Faculty of Nutrition Sciences and Food Technology/National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3. Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. 4. Cancer Institute, Tehran University of Medical Sciences/Day General Hospital, Tehran, Iran. 5. Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 6. Department of Clinical Epidemiology/Safety Promotion and Injury Prevention Research Centre, Faculty of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract
BACKGROUND/ OBJECTIVES: Folate, pyridoxine and cobalamin are coenzymatically essential in one-carbon methyl metabolism, and their deficiencies could explain some alterations during breast carcinogenesis. We aimed to evaluate the validity of folate, pyridoxine and cobalamin estimates from a food frequency questionnaire (FFQ) on the basis of their corresponding fasting plasma biomarkers, in breast cancer (BC) patients. SUBJECTS/ METHODS: In a prospective, consecutive case series, 149 women with primary BC aged between 30 and 69 years as a representative sample of Iranian women with BC were recruited. The 136-item FFQ was used for the validity assay. Fasting plasma folate and cobalamin were tested by automated electrochemiluminescence. The high-pressure liquid chromatography with fluorescence detection was used to determine the plasma levels of pyridoxal-5'-phosphate (PLP) and total homocysteine (tHcy). RESULTS: Area under the curve (AUC) for assessing the diagnostic accuracy of folate-related data through an FFQ was 0.74 (P<0.01) in the reference model (folate plasma level<5.9 ng/ml), with sensitivity and specificity of 68% and 63%, respectively. The positive and negative predictive values (PPV and NPV) were 96.9% and 96.8%, respectively. The AUC for cobalamin intake in the reference model (plasma cobalamin<260 pmol/l) was 0.64 (P<0.01), with 60% sensitivity and 61% specificity. Although tHcy ≥10.0 μmol/l was used as reference indicator, the folate intake (AUC=0.71, P<0.01) and cobalamin intake status (AUC=0.67, P<0.05) were also determined appropriately by FFQ. CONCLUSIONS: Dietary folate and cobalamin estimates from FFQ were significantly correlated with their fasting plasma concentrations. Our data supported the validity of new FFQ to rank individuals by dietary intake status of folate and cobalamin.
BACKGROUND/ OBJECTIVES:Folate, pyridoxine and cobalamin are coenzymatically essential in one-carbon methyl metabolism, and their deficiencies could explain some alterations during breast carcinogenesis. We aimed to evaluate the validity of folate, pyridoxine and cobalamin estimates from a food frequency questionnaire (FFQ) on the basis of their corresponding fasting plasma biomarkers, in breast cancer (BC) patients. SUBJECTS/ METHODS: In a prospective, consecutive case series, 149 women with primary BC aged between 30 and 69 years as a representative sample of Iranian women with BC were recruited. The 136-item FFQ was used for the validity assay. Fasting plasma folate and cobalamin were tested by automated electrochemiluminescence. The high-pressure liquid chromatography with fluorescence detection was used to determine the plasma levels of pyridoxal-5'-phosphate (PLP) and total homocysteine (tHcy). RESULTS: Area under the curve (AUC) for assessing the diagnostic accuracy of folate-related data through an FFQ was 0.74 (P<0.01) in the reference model (folate plasma level<5.9 ng/ml), with sensitivity and specificity of 68% and 63%, respectively. The positive and negative predictive values (PPV and NPV) were 96.9% and 96.8%, respectively. The AUC for cobalamin intake in the reference model (plasma cobalamin<260 pmol/l) was 0.64 (P<0.01), with 60% sensitivity and 61% specificity. Although tHcy ≥10.0 μmol/l was used as reference indicator, the folate intake (AUC=0.71, P<0.01) and cobalamin intake status (AUC=0.67, P<0.05) were also determined appropriately by FFQ. CONCLUSIONS: Dietary folate and cobalamin estimates from FFQ were significantly correlated with their fasting plasma concentrations. Our data supported the validity of new FFQ to rank individuals by dietary intake status of folate and cobalamin.
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