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.