METHODS: This study was conducted within the European Prospective Investigation into Nutrition and Cancer cohort, comprising male and female participants from 10 European countries. Between 1992 and 2000, there were 477,312 participants without cancer who completed a dietary questionnaire and were followed up to determine pancreatic cancer incidence. Coffee and tea intake was calibrated with a 24-hour dietary recall. Adjusted hazard ratios (HRs) were computed using multivariable Cox regression.
RESULTS: During a mean follow-up period of 11.6 y, 865 first incidences of pancreatic cancers were reported. When divided into fourths, neither total intake of coffee (HR, 1.03; 95% confidence interval [CI], 0.83-1.27; high vs low intake), decaffeinated coffee (HR, 1.12; 95% CI, 0.76-1.63; high vs low intake), nor tea were associated with risk of pancreatic cancer (HR, 1.22, 95% CI, 0.95-1.56; high vs low intake). Moderately low intake of caffeinated coffee was associated with an increased risk of pancreatic cancer (HR, 1.33; 95% CI, 1.02-1.74), compared with low intake. However, no graded dose response was observed, and the association attenuated after restriction to histologically confirmed pancreatic cancers.
CONCLUSIONS: Based on an analysis of data from the European Prospective Investigation into Nutrition and Cancer cohort, total coffee, decaffeinated coffee, and tea consumption are not related to the risk of pancreatic cancer.
METHODS: A total of 1,055 colorectal cancer cases (colon n = 659; rectal n = 396) were matchced (1:1) to control subjects. Circulating glycer-AGEs were measured by a competitive ELISA. Multivariable conditional logistic regression models were used to calculate ORs and 95% confidence intervals (95% CI), adjusting for potential confounding factors, including smoking, alcohol, physical activity, body mass index, and diabetes status.
RESULTS: Elevated glycer-AGEs levels were not associated with colorectal cancer risk (highest vs. lowest quartile, 1.10; 95% CI, 0.82-1.49). Subgroup analyses showed possible divergence by anatomical subsites (OR for colon cancer, 0.83; 95% CI, 0.57-1.22; OR for rectal cancer, 1.90; 95% CI, 1.14-3.19; Pheterogeneity = 0.14).
CONCLUSIONS: In this prospective study, circulating glycer-AGEs were not associated with risk of colon cancer, but showed a positive association with the risk of rectal cancer.
IMPACT: Further research is needed to clarify the role of toxic products of carbohydrate metabolism and energy excess in colorectal cancer development.
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
METHODS: A total of 1,065 incident colorectal cancer cases (colon, n = 667; rectal, n = 398) were matched (1:1) to control subjects. Serum flagellin- and LPS-specific IgA and IgG levels were quantitated by ELISA. Multivariable conditional logistic regression models were used to calculate ORs and 95% confidence intervals (CI), adjusting for multiple relevant confouding factors.
RESULTS: Overall, elevated anti-LPS and anti-flagellin biomarker levels were not associated with colorectal cancer risk. After testing potential interactions by various factors relevant for colorectal cancer risk and anti-LPS and anti-flagellin, sex was identified as a statistically significant interaction factor (Pinteraction < 0.05 for all the biomarkers). Analyses stratified by sex showed a statistically significant positive colorectal cancer risk association for men (fully-adjusted OR for highest vs. lowest quartile for total anti-LPS + flagellin, 1.66; 95% CI, 1.10-2.51; Ptrend, 0.049), whereas a borderline statistically significant inverse association was observed for women (fully-adjusted OR, 0.70; 95% CI, 0.47-1.02; Ptrend, 0.18).
CONCLUSION: In this prospective study on European populations, we found bacterial exposure levels to be positively associated to colorectal cancer risk among men, whereas in women, a possible inverse association may exist.
IMPACT: Further studies are warranted to better clarify these preliminary observations.
METHODS: A nested-case control study was conducted within the prospective EPIC cohort (>520,000 participants, 10 European countries). After a mean 7.5 mean years of follow-up, 121 hepatocellular carcinoma (HCC), 34 intrahepatic bile duct (IHBC) and 131 gallbladder and biliary tract (GBTC) cases were identified and matched to 2 controls each. Circulating biomarkers were measured in serum taken at recruitment into the cohort, prior to cancer diagnosis. Multivariable adjusted conditional logistic regression was used to calculate odds ratios and 95% confidence intervals (OR; 95%CI).
RESULTS: In multivariable models, 1SD increase of each log-transformed biomarker was positively associated with HCC risk (OR(GGT)=4.23, 95%CI:2.72-6.59; OR(ALP)=3.43, 95%CI:2.31-5.10;OR(AST)=3.00, 95%CI:2.04-4.42; OR(ALT)=2.69, 95%CI:1.89-3.84; OR(Bilirubin)=2.25, 95%CI:1.58-3.20). Each liver enzyme (OR(GGT)=4.98; 95%CI:1.75-14.17; OR(AST)=3.10, 95%CI:1.04-9.30; OR(ALT)=2.86, 95%CI:1.26-6.48, OR(ALP)=2.31, 95%CI:1.10-4.86) but not bilirubin (OR(Bilirubin)=1.46,95%CI:0.85-2.51) showed a significant association with IHBC. Only ALP was significantly associated with GBTC risk (OR(ALP)=1.59, 95%CI:1.20-2.09).
CONCLUSION: This study shows positive associations between circulating liver biomarkers in sera collected prior to cancer diagnoses and the risks of developing HCC or IHBC, but not GBTC.
OBJECTIVE: To examine the association between total, sugar-sweetened, and artificially sweetened soft drink consumption and subsequent total and cause-specific mortality.
DESIGN, SETTING, AND PARTICIPANTS: This population-based cohort study involved participants (n = 451 743 of the full cohort) in the European Prospective Investigation into Cancer and Nutrition (EPIC), an ongoing, large multinational cohort of people from 10 European countries (Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom), with participants recruited between January 1, 1992, and December 31, 2000. Excluded participants were those who reported cancer, heart disease, stroke, or diabetes at baseline; those with implausible dietary intake data; and those with missing soft drink consumption or follow-up information. Data analyses were performed from February 1, 2018, to October 1, 2018.
EXPOSURE: Consumption of total, sugar-sweetened, and artificially sweetened soft drinks.
MAIN OUTCOMES AND MEASURES: Total mortality and cause-specific mortality. Hazard ratios (HRs) and 95% CIs were estimated using multivariable Cox proportional hazards regression models adjusted for other mortality risk factors.
RESULTS: In total, 521 330 individuals were enrolled. Of this total, 451 743 (86.7%) were included in the study, with a mean (SD) age of 50.8 (9.8) years and with 321 081 women (71.1%). During a mean (range) follow-up of 16.4 (11.1 in Greece to 19.2 in France) years, 41 693 deaths occurred. Higher all-cause mortality was found among participants who consumed 2 or more glasses per day (vs consumers of <1 glass per month) of total soft drinks (hazard ratio [HR], 1.17; 95% CI, 1.11-1.22; P
OBJECTIVE: We aimed to evaluate the potential mediating roles of inflammatory, metabolic, liver injury, and iron metabolism biomarkers on the association between coffee intake and the primary form of liver cancer-hepatocellular carcinoma (HCC).
DESIGN: We conducted a prospective nested case-control study within the European Prospective Investigation into Cancer and Nutrition among 125 incident HCC cases matched to 250 controls using an incidence-density sampling procedure. The association of coffee intake with HCC risk was evaluated by using multivariable-adjusted conditional logistic regression that accounted for smoking, alcohol consumption, hepatitis infection, and other established liver cancer risk factors. The mediating effects of 21 biomarkers were evaluated on the basis of percentage changes and associated 95% CIs in the estimated regression coefficients of models with and without adjustment for biomarkers individually and in combination.
RESULTS: The multivariable-adjusted RR of having ≥4 cups (600 mL) coffee/d compared with <2 cups (300 mL)/d was 0.25 (95% CI: 0.11, 0.62; P-trend = 0.006). A statistically significant attenuation of the association between coffee intake and HCC risk and thereby suspected mediation was confirmed for the inflammatory biomarker IL-6 and for the biomarkers of hepatocellular injury glutamate dehydrogenase, alanine aminotransferase, aspartate aminotransferase (AST), γ-glutamyltransferase (GGT), and total bilirubin, which-in combination-attenuated the regression coefficients by 72% (95% CI: 7%, 239%). Of the investigated biomarkers, IL-6, AST, and GGT produced the highest change in the regression coefficients: 40%, 56%, and 60%, respectively.
CONCLUSION: These data suggest that the inverse association of coffee intake with HCC risk was partly accounted for by biomarkers of inflammation and hepatocellular injury.
METHODS: The association between the WCRF/AICR score (score range 0-6 in men and 0-7 in women; higher scores indicate greater concordance) assessed on average 6.4 years before diagnosis and CRC-specific (n = 872) and overall mortality (n = 1,113) was prospectively examined among 3,292 participants diagnosed with CRC in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (mean follow-up time after diagnosis 4.2 years). Multivariable Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for mortality.
RESULTS: The HRs (95% CIs) for CRC-specific mortality among participants in the second (score range in men/women: 2.25-2.75/3.25-3.75), third (3-3.75/4-4.75), and fourth (4-6/5-7) categories of the score were 0.87 (0.72-1.06), 0.74 (0.61-0.90), and 0.70 (0.56-0.89), respectively (P for trend <0.0001), compared to participants with the lowest concordance with the recommendations (category 1 of the score: 0-2/0-3). Similar HRs for overall mortality were observed (P for trend 0.004). Meeting the recommendations on body fatness and plant food consumption were associated with improved survival among CRC cases in mutually adjusted models.
CONCLUSIONS: Greater concordance with the WCRF/AICR recommendations on diet, physical activity, and body fatness prior to CRC diagnosis is associated with improved survival among CRC patients.
METHODS: Dietary intake of fish (total, fatty/oily, lean/white) and n-3 LC-PUFA were estimated by food frequency questionnaires given to 521,324 participants in the EPIC study; among these, 6291 individuals developed CRC (median follow up, 14.9 years). Levels of phospholipid LC-PUFA were measured by gas chromatography in plasma samples from a sub-group of 461 CRC cases and 461 matched individuals without CRC (controls). Multivariable Cox proportional hazards and conditional logistic regression models were used to calculate hazard ratios (HRs) and odds ratios (ORs), respectively, with 95% CIs.
RESULTS: Total intake of fish (HR for quintile 5 vs 1, 0.88; 95% CI, 0.80-0.96; Ptrend = .005), fatty fish (HR for quintile 5 vs 1, 0.90; 95% CI, 0.82-0.98; Ptrend = .009), and lean fish (HR for quintile 5 vs 1, 0.91; 95% CI, 0.83-1.00; Ptrend = .016) were inversely associated with CRC incidence. Intake of total n-3 LC-PUFA (HR for quintile 5 vs 1, 0.86; 95% CI, 0.78-0.95; Ptrend = .010) was also associated with reduced risk of CRC, whereas dietary ratio of n-6:n-3 LC-PUFA was associated with increased risk of CRC (HR for quintile 5 vs 1, 1.31; 95% CI, 1.18-1.45; Ptrend < .001). Plasma levels of phospholipid n-3 LC-PUFA was not associated with overall CRC risk, but an inverse trend was observed for proximal compared with distal colon cancer (Pheterogeneity = .026).
CONCLUSIONS: In an analysis of dietary patterns of participants in the EPIC study, we found regular consumption of fish, at recommended levels, to be associated with a lower risk of CRC, possibly through exposure to n-3 LC-PUFA. Levels of n-3 LC-PUFA in plasma were not associated with CRC risk, but there may be differences in risk at different regions of the colon.
METHODS: Using HPV serology as a marker of HPV-related cancer, we examined the interaction between smoking and HPV16 in 459 oropharyngeal (and 1445 oral cavity and laryngeal) cancer patients and 3024 control participants from two large European multi-centre studies. Odds ratios and credible intervals [CrI], adjusted for potential confounders, were estimated using Bayesian logistic regression.
RESULTS: Both smoking [odds ratio (OR [CrI]: 6.82 [4.52, 10.29]) and HPV seropositivity (OR [CrI]: 235.69 [99.95, 555.74]) were independently associated with oropharyngeal cancer. The joint association of smoking and HPV seropositivity was consistent with that expected on the additive scale (synergy index [CrI]: 1.32 [0.51, 3.45]), suggesting they act as independent risk factors for oropharyngeal cancer.
CONCLUSIONS: Smoking was consistently associated with increase in oropharyngeal cancer risk in models stratified by HPV16 seropositivity. In addition, we report that the prevalence of oropharyngeal cancer increases with smoking for both HPV16-positive and HPV16-negative persons. The impact of smoking on HPV16-positive oropharyngeal cancer highlights the continued need for smoking cessation programmes for primary prevention of head and neck cancer.
METHODS: We analysed data from 264,906 European adults from the EPIC prospective cohort study, aged between 40 and 70 years at the time of recruitment. Flexible parametric survival models were used to model risk of death conditional on risk factors, and survival functions and attributable fractions (AF) for deaths prior to age 70 years were calculated based on the fitted models.
RESULTS: We identified 11,930 deaths which occurred before the age of 70. The AF for premature mortality for smoking was 31 % (95 % confidence interval (CI), 31-32 %) and 14 % (95 % CI, 12-16 %) for poor diet. Important contributions were also observed for overweight and obesity measured by waist-hip ratio (10 %; 95 % CI, 8-12 %) and high blood pressure (9 %; 95 % CI, 7-11 %). AFs for physical inactivity and excessive alcohol intake were 7 % and 4 %, respectively. Collectively, the AF for all six risk factors was 57 % (95 % CI, 55-59 %), being 35 % (95 % CI, 32-37 %) among never smokers and 74 % (95 % CI, 73-75 %) among current smokers.
CONCLUSIONS: While smoking remains the predominant risk factor for premature death in Europe, poor diet, overweight and obesity, hypertension, physical inactivity, and excessive alcohol consumption also contribute substantially. Any attempt to minimise premature deaths will ultimately require all six factors to be addressed.
OBJECTIVE: We used a nutrient-wide association study approach to systematically test the association between dietary factors and invasive EOC risk while accounting for multiple hypothesis testing by using the false discovery rate and evaluated the findings in an independent cohort.
DESIGN: We assessed dietary intake amounts of 28 foods/food groups and 29 nutrients estimated by using dietary questionnaires in the EPIC (European Prospective Investigation into Cancer and Nutrition) study (n = 1095 cases). We selected 4 foods/nutrients that were statistically significantly associated with EOC risk when comparing the extreme quartiles of intake in the EPIC study (false discovery rate = 0.43) and evaluated these factors in the NLCS (Netherlands Cohort Study; n = 383 cases). Cox regression models were used to estimate HRs and 95% CIs.
RESULTS: None of the 4 dietary factors that were associated with EOC risk in the EPIC study (cholesterol, polyunsaturated and saturated fat, and bananas) were statistically significantly associated with EOC risk in the NLCS; however, in meta-analysis of the EPIC study and the NLCS, we observed a higher risk of EOC with a high than with a low intake of saturated fat (quartile 4 compared with quartile 1; overall HR: 1.21; 95% CI: 1.04, 1.41).
CONCLUSION: In the meta-analysis of both studies, there was a higher risk of EOC with a high than with a low intake of saturated fat.
METHODS: In the European Prospective Investigation into Cancer and Nutrition study, we used multivariable joint Cox proportional hazards models, which accounted for tumors at different anatomical sites (proximal colon, distal colon, and rectum) as competing risks, to examine the relationships between 14 established/suspected lifestyle, anthropometric, and reproductive/menstrual risk factors with colorectal cancer risk. Heterogeneity across sites was tested using Wald tests.
RESULTS: After a median of 14.9 years of follow-up of 521,330 men and women, 6291 colorectal cancer cases occurred. Physical activity was related inversely to proximal colon and distal colon cancer, but not to rectal cancer (P heterogeneity = .03). Height was associated positively with proximal and distal colon cancer only, but not rectal cancer (P heterogeneity = .0001). For men, but not women, heterogeneous relationships were observed for body mass index (P heterogeneity = .008) and waist circumference (P heterogeneity = .03), with weaker positive associations found for rectal cancer, compared with proximal and distal colon cancer. Current smoking was associated with a greater risk of rectal and proximal colon cancer, but not distal colon cancer (P heterogeneity = .05). No heterogeneity by anatomical site was found for alcohol consumption, diabetes, nonsteroidal anti-inflammatory drug use, and reproductive/menstrual factors.
CONCLUSIONS: The relationships between physical activity, anthropometry, and smoking with colorectal cancer risk differed by subsite, supporting the hypothesis that tumors in different anatomical regions may have distinct etiologies.