METHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC), pre-diagnostic unconjugated bilirubin (UCB, the main component of total bilirubin) concentrations were measured by high-performance liquid chromatography in plasma samples of 1386 CRC cases and their individually matched controls. Additionally, 115 single-nucleotide polymorphisms (SNPs) robustly associated (P
METHODS AND FINDINGS: We followed a cohort of 308,036 women recruited in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study. At enrollment, participants completed a questionnaire and provided serum. After a 9-year median follow-up, 261 ICC and 804 CIN3/CIS cases were reported. In a nested case-control study, the sera from 609 cases and 1,218 matched controls were tested for L1 antibodies against HPV types 11,16,18,31,33,35,45,52,58, and antibodies against Chlamydia trachomatis and Human herpesvirus 2. Multivariate analyses were performed to estimate hazard ratios (HR), odds ratios (OR) and corresponding 95% confidence intervals (CI). The cohort analysis showed that number of full-term pregnancies was positively associated with CIN3/CIS risk (p-trend = 0.03). Duration of oral contraceptives use was associated with a significantly increased risk of both CIN3/CIS and ICC (HR = 1.6 and HR = 1.8 respectively for ≥ 15 years versus never use). Ever use of menopausal hormone therapy was associated with a reduced risk of ICC (HR = 0.5, 95%CI: 0.4-0.8). A non-significant reduced risk of ICC with ever use of intrauterine devices (IUD) was found in the nested case-control analysis (OR = 0.6). Analyses restricted to all cases and HPV seropositive controls yielded similar results, revealing a significant inverse association with IUD for combined CIN3/CIS and ICC (OR = 0.7).
CONCLUSIONS: Even though HPV is the necessary cause of CC, our results suggest that several hormonal factors are risk factors for cervical carcinogenesis. Adherence to current cervical cancer screening guidelines should minimize the increased risk of CC associated with these hormonal risk factors.
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: A nutrient-wide association study was conducted to systematically and comprehensively evaluate the associations between 92 foods or nutrients and risk of prostate cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). Cox proportional hazard regression models adjusted for total energy intake, smoking status, body mass index, physical activity, diabetes and education were used to estimate hazard ratios and 95% confidence intervals for standardized dietary intakes. As in genome-wide association studies, correction for multiple comparisons was applied using the false discovery rate (FDR
METHODS: We conducted a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate C-reactive protein (CRP), IL6, and EOC risk by tumor characteristics. A total of 754 eligible EOC cases were identified; two controls (n = 1,497) were matched per case. We used multivariable conditional logistic regression to assess associations.
RESULTS: CRP and IL6 were not associated with overall EOC risk. However, consistent with prior research, CRP >10 versus CRP ≤1 mg/L was associated with higher overall EOC risk [OR, 1.67 (1.03-2.70)]. We did not observe significant associations or heterogeneity in analyses by tumor characteristics. In analyses stratified by waist circumference, inflammatory markers were associated with higher risk among women with higher waist circumference; no association was observed for women with normal waist circumference [e.g., IL6: waist ≤80: ORlog2, 0.97 (0.81-1.16); waist >88: ORlog2, 1.78 (1.28-2.48), Pheterogeneity ≤ 0.01].
CONCLUSIONS: Our data suggest that high CRP is associated with increased risk of overall EOC, and that IL6 and CRP may be associated with EOC risk among women with higher adiposity.
IMPACT: Our data add to global evidence that ovarian carcinogenesis may be promoted by an inflammatory milieu.
METHODS: A nested case-control study in nonsmoking postmenopausal women (334 cases, 417 controls) was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Unconditional logistic regression models were used to estimate ORs and 95% confidence intervals (CI) for the association between HbAA, HbGA, HbAA+HbGA, and HbGA/HbAA and EOC and invasive serous EOC risk.
RESULTS: No overall associations were observed between biomarkers of acrylamide exposure analyzed in quintiles and EOC risk; however, positive associations were observed between some middle quintiles of HbGA and HbAA+HbGA. Elevated but nonstatistically significant ORs for serous EOC were observed for HbGA and HbAA+HbGA (ORQ5vsQ1, 1.91; 95% CI, 0.96-3.81 and ORQ5vsQ1, 1.90; 95% CI, 0.94-3.83, respectively); however, no linear dose-response trends were observed.
CONCLUSION: This EPIC nested case-control study failed to observe a clear association between biomarkers of acrylamide exposure and the risk of EOC or invasive serous EOC.
IMPACT: It is unlikely that dietary acrylamide exposure increases ovarian cancer risk; however, additional studies with larger sample size should be performed to exclude any possible association with EOC risk.
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: 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.