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Carotenoids, retinol, tocopherols, and prostate cancer risk: pooled analysis of 15 studies - PubMed

. 2015 Nov;102(5):1142-57.

doi: 10.3945/ajcn.115.114306. Epub 2015 Oct 7.

Paul N Appleby  2 Ruth C Travis  2 Demetrius Albanes  3 Anthony J Alberg  4 Aurelio Barricarte  5 Amanda Black  3 Heiner Boeing  6 H Bas Bueno-de-Mesquita  7 June M Chan  8 Chu Chen  9 Michael B Cook  3 Jenny L Donovan  10 Pilar Galan  11 Rebecca Gilbert  10 Graham G Giles  12 Edward Giovannucci  13 Gary E Goodman  14 Phyllis J Goodman  15 Marc J Gunter  16 Freddie C Hamdy  17 Markku Heliövaara  18 Kathy J Helzlsouer  19 Brian E Henderson  20 Serge Hercberg  11 Judy Hoffman-Bolton  21 Robert N Hoover  3 Mattias Johansson  22 Kay-Tee Khaw  23 Irena B King  24 Paul Knekt  18 Laurence N Kolonel  25 Loic Le Marchand  25 Satu Männistö  18 Richard M Martin  26 Haakon E Meyer  27 Alison M Mondul  3 Kristin A Moy  3 David E Neal  28 Marian L Neuhouser  29 Domenico Palli  30 Elizabeth A Platz  31 Camille Pouchieu  12 Harri Rissanen  18 Jeannette M Schenk  32 Gianluca Severi  12 Meir J Stampfer  13 Anne Tjønneland  33 Mathilde Touvier  11 Antonia Trichopoulou  34 Stephanie J Weinstein  3 Regina G Ziegler  3 Cindy Ke Zhou  3 Naomi E Allen  35 Endogenous Hormones Nutritional Biomarkers Prostate Cancer Collaborative Group

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Carotenoids, retinol, tocopherols, and prostate cancer risk: pooled analysis of 15 studies

Timothy J Key et al. Am J Clin Nutr. 2015 Nov.

Abstract

Background: Individual studies have suggested that circulating carotenoids, retinol, or tocopherols may be associated with prostate cancer risk, but the studies have not been large enough to provide precise estimates of associations, particularly by stage and grade of disease.

Objective: The objective of this study was to conduct a pooled analysis of the associations of the concentrations of 7 carotenoids, retinol, α-tocopherol, and γ-tocopherol with risk of prostate cancer and to describe whether any associations differ by stage or grade of the disease or other factors.

Design: Principal investigators of prospective studies provided individual participant data for prostate cancer cases and controls. Risk by study-specific fifths of each biomarker was estimated by using multivariable-adjusted conditional logistic regression in matched case-control sets.

Results: Data were available for up to 11,239 cases (including 1654 advanced stage and 1741 aggressive) and 18,541 controls from 15 studies. Lycopene was not associated with overall risk of prostate cancer, but there was statistically significant heterogeneity by stage of disease, and the OR for aggressive disease for the highest compared with the lowest fifth of lycopene was 0.65 (95% CI: 0.46, 0.91; P-trend = 0.032). No other carotenoid was significantly associated with overall risk of prostate cancer or with risk of advanced-stage or aggressive disease. For retinol, the OR for the highest compared with the lowest fifth was 1.13 (95% CI: 1.04, 1.22; P-trend = 0.015). For α-tocopherol, the OR for the highest compared with the lowest fifth was 0.86 (95% CI: 0.78, 0.94; P-trend < 0.001), with significant heterogeneity by stage of disease; the OR for aggressive prostate cancer was 0.74 (95% CI: 0.59, 0.92; P-trend = 0.001). γ-Tocopherol was not associated with risk.

Conclusions: Overall prostate cancer risk was positively associated with retinol and inversely associated with α-tocopherol, and risk of aggressive prostate cancer was inversely associated with lycopene and α-tocopherol. Whether these associations reflect causal relations is unclear.

Keywords: biomarkers; carotenoids; nested case-control study; pooled analysis; prostate cancer; retinol; tocopherols; vitamin A; vitamin E.

© 2015 American Society for Nutrition.

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Figures

FIGURE 1
FIGURE 1

ORs for prostate cancer associated with carotenoids, retinol, and tocopherols. The black squares indicate the ORs in study-specific fifths, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The diamonds show the OR for an increase in concentration from the 10th to the 90th percentile, and the widths of the diamonds show the 95% CIs. The χ2 tests for linear trend (Ptr) were calculated scoring the fifths as 0, 0.25, 0.5, 0.75, and 1. Estimates are from conditional logistic regression on case-control sets matched within each study and adjusted for age, marital status, educational attainment, smoking, height, and BMI.

FIGURE 2
FIGURE 2

ORs for prostate cancer associated with lycopene concentration, according to characteristics of cases and controls. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fifths of lycopene concentration in controls by a continuous variable scored as 0, 0.25, 0.5, 0.75, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of lycopene with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case-control sets matched within each study and adjusted for age, marital status, educational attainment, smoking, height and BMI. PSA, prostate-specific antigen.

FIGURE 3
FIGURE 3

ORs for prostate cancer associated with retinol concentration, according to characteristics of cases and controls. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fifths of retinol concentration in controls by a continuous variable scored as 0, 0.25, 0.5, 0.75, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of retinol with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case-control sets matched within each study and adjusted for age, marital status, educational attainment, smoking, height and BMI. PSA, prostate-specific antigen.

FIGURE 4
FIGURE 4

ORs for prostate cancer associated with α-tocopherol concentration, according to characteristics of cases and controls. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fifths of α-tocopherol concentration in controls by a continuous variable scored as 0, 0.25, 0.5, 0.75, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of α-tocopherol with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case-control sets matched within each study and adjusted for age, marital status, educational attainement, smoking, height and BMI. PSA, prostate-specific antigen.

FIGURE 5
FIGURE 5

ORs for aggressive prostate cancer associated with carotenoids, retinol, and tocopherols. The black squares indicate the ORs in study-specific fifths, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The diamonds show the OR for an increase in concentration from the 10th to the 90th percentile, and the widths of the diamonds show the 95% CIs. The χ2 tests for linear trend (Ptr) were calculated by scoring the fifths as 0, 0.25, 0.5, 0.75, and 1. Estimates are from conditional logistic regression on case-control sets matched within each study and adjusted for age, marital status, educational attainment, smoking, height and BMI.

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