STUDY DESIGN: Individual data on SRH and important covariates were obtained for 424,791 European and United States residents, ≥60 years at recruitment (1982-2008), in eight prospective studies in the Consortium on Health and Ageing: Network of Cohorts in Europe and the United States (CHANCES). In each study, adjusted mortality ratios (hazard ratios, HRs) in relation to SRH were calculated and subsequently combined with random-effect meta-analyses.
MAIN OUTCOME MEASURES: All-cause, cardiovascular and cancer mortality.
RESULTS: Within the median 12.5 years of follow-up, 93,014 (22%) deaths occurred. SRH "fair" or "poor" vs. "at-least-good" was associated with increased mortality: HRs 1.46 (95% CI 1·23-1.74) and 2.31 (1.79-2.99), respectively. These associations were evident: for cardiovascular and, to a lesser extent, cancer mortality, and within-study, within-subgroup analyses. Accounting for lifestyle, sociodemographic, somatometric factors and, subsequently, for medical history explained only a modest amount of the unadjusted associations. Factors favourably associated with SRH were: sex (males), age (younger-old), education (high), marital status (married/cohabiting), physical activity (active), body mass index (non-obese), alcohol consumption (low to moderate) and previous morbidity (absence).
CONCLUSION: SRH provides a quick and simple tool for assessing health and identifying groups of elders at risk of early mortality that may be useful also in clinical settings. Modifying determinants of favourably rating health, e.g. by increasing physical activity and/or by eliminating obesity, may be important for older adults to "feel healthy" and "be healthy".
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 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 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: This study evaluated the associations of plasma carotenoid, retinol, tocopherol, and vitamin C concentrations and risk of breast cancer.
DESIGN: In a nested case-control study within the European Prospective Investigation into Cancer and Nutrition cohort, 1502 female incident breast cancer cases were included, with an oversampling of premenopausal (n = 582) and estrogen receptor-negative (ER-) cases (n = 462). Controls (n = 1502) were individually matched to cases by using incidence density sampling. Prediagnostic samples were analyzed for α-carotene, β-carotene, lycopene, lutein, zeaxanthin, β-cryptoxanthin, retinol, α-tocopherol, γ-tocopherol, and vitamin C. Breast cancer risk was computed according to hormone receptor status and age at diagnosis (proxy for menopausal status) by using conditional logistic regression and was further stratified by smoking status, alcohol consumption, and body mass index (BMI). All statistical tests were 2-sided.
RESULTS: In quintile 5 compared with quintile 1, α-carotene (OR: 0.61; 95% CI: 0.39, 0.98) and β-carotene (OR: 0.41; 95% CI: 0.26, 0.65) were inversely associated with risk of ER- breast tumors. The other analytes were not statistically associated with ER- breast cancer. For estrogen receptor-positive (ER+) tumors, no statistically significant associations were found. The test for heterogeneity between ER- and ER+ tumors was statistically significant only for β-carotene (P-heterogeneity = 0.03). A higher risk of breast cancer was found for retinol in relation to ER-/progesterone receptor-negative tumors (OR: 2.37; 95% CI: 1.20, 4.67; P-heterogeneity with ER+/progesterone receptor positive = 0.06). We observed no statistically significant interaction between smoking, alcohol, or BMI and all investigated plasma analytes (based on tertile distribution).
CONCLUSION: Our results indicate that higher concentrations of plasma β-carotene and α-carotene are associated with lower breast cancer risk of ER- tumors.
OBJECTIVE: This study aimed to investigate the association between vegetable and fruit intake and steroid hormone receptor-defined breast cancer risk.
DESIGN: A total of 335,054 female participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort were included in this study (mean ± SD age: 50.8 ± 9.8 y). Vegetable and fruit intake was measured by country-specific questionnaires filled out at recruitment between 1992 and 2000 with the use of standardized procedures. Cox proportional hazards models were stratified by age at recruitment and study center and were adjusted for breast cancer risk factors.
RESULTS: After a median follow-up of 11.5 y (IQR: 10.1-12.3 y), 10,197 incident invasive breast cancers were diagnosed [3479 estrogen and progesterone receptor positive (ER+PR+); 1021 ER and PR negative (ER-PR-)]. Compared with the lowest quintile, the highest quintile of vegetable intake was associated with a lower risk of overall breast cancer (HRquintile 5-quintile 1: 0.87; 95% CI: 0.80, 0.94). Although the inverse association was most apparent for ER-PR- breast cancer (ER-PR-: HRquintile 5-quintile 1: 0.74; 95% CI: 0.57, 0.96; P-trend = 0.03; ER+PR+: HRquintile 5-quintile 1: 0.91; 95% CI: 0.79, 1.05; P-trend = 0.14), the test for heterogeneity by hormone receptor status was not significant (P-heterogeneity = 0.09). Fruit intake was not significantly associated with total and hormone receptor-defined breast cancer risk.
CONCLUSION: This study supports evidence that a high vegetable intake is associated with lower (mainly hormone receptor-negative) breast cancer risk.
RESULTS: Higher total neopterin concentrations were associated with reduced HDLC (9.7 %, 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: We used three single nucleotide polymorphisms (SNPs) (rs8176746, rs505922, and rs8176704) to determine ABO genotype in 2,774 aggressive prostate cancer cases and 4,443 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). Unconditional logistic regression was used to calculate age and study-adjusted odds ratios and 95% confidence intervals for the association between blood type, genotype, and risk of aggressive prostate cancer (Gleason score ≥8 or locally advanced/metastatic disease (stage T3/T4/N1/M1).
RESULTS: We found no association between ABO blood type and risk of aggressive prostate cancer (Type A: OR = 0.97, 95%CI = 0.87-1.08; Type B: OR = 0.92, 95%CI =n0.77-1.09; Type AB: OR = 1.25, 95%CI = 0.98-1.59, compared to Type O, respectively). Similarly, there was no association between "dose" of A or B alleles and aggressive prostate cancer risk.
CONCLUSIONS: ABO blood type was not associated with risk of aggressive prostate cancer.
METHODS: The analysis was performed within the European Investigation into Cancer and Nutrition prospective cohort study, which enrolled >500,000 women and men from 1992 to 2000, who were residing in a given town/geographic area in 10 European countries. The current analysis included 322,972 eligible women aged 25-70 years with 99 % complete follow-up for vital status. We assessed reproductive characteristics reported at the study baseline including parity, age at the first birth, breastfeeding, infertility, oral contraceptive use, age at menarche and menopause, total ovulatory years, and history of oophorectomy/hysterectomy. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for mortality were determined using Cox proportional hazards regression models adjusted for menopausal status, body mass index, physical activity, education level, and smoking status/intensity and duration.
RESULTS: During a mean follow-up of 12.9 years, 14,383 deaths occurred. The HR (95 % CI) for risk of all-cause mortality was lower in parous versus nulliparous women (0.80; 0.76-0.84), in women who had ever versus never breastfed (0.92; 0.87-0.97), in ever versus never users of oral contraceptives (among non-smokers; 0.90; 0.86-0.95), and in women reporting a later age at menarche (≥15 years versus <12; 0.90; 0.85-0.96; P for trend = 0.038).
CONCLUSIONS: Childbirth, breastfeeding, oral contraceptive use, and a later age at menarche were associated with better health outcomes. These findings may contribute to the development of improved strategies to promote better long-term health in women.
METHODS: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort.
RESULTS: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis.
CONCLUSION: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.
SUMMARY ANSWER: Although there was no overall association between diabetes and age at menopause, our study suggests that early-onset diabetes may accelerate menopause.
WHAT IS KNOWN ALREADY: Today, more women of childbearing age are being diagnosed with diabetes, but little is known about the impact of diabetes on reproductive health.
STUDY DESIGN, SIZE, DURATION: We investigated the impact of diabetes on age at natural menopause (ANM) in 258 898 women from the European Prospective Investigation into Cancer and Nutrition (EPIC), enrolled between 1992 and 2000.
PARTICIPANTS/MATERIALS, SETTING, METHODS: Determinant and outcome information was obtained through questionnaires. Time-dependent Cox regression analyses were used to estimate the associations of diabetes and age at diabetes diagnosis with ANM, stratified by center and adjusted for age, smoking, reproductive and diabetes risk factors and with age from birth to menopause or censoring as the underlying time scale.
MAIN RESULTS AND THE ROLE OF CHANCE: Overall, no association between diabetes and ANM was found (hazard ratio (HR) = 0.94; 95% confidence interval (CI) 0.89-1.01). However, women with diabetes before the age of 20 years had an earlier menopause (10-20 years: HR = 1.43; 95% CI 1.02-2.01, <10 years: HR = 1.59; 95% CI 1.03-2.43) compared with non-diabetic women, whereas women with diabetes at age 50 years and older had a later menopause (HR = 0.81; 95% CI 0.70-0.95). None of the other age groups were associated with ANM.
LIMITATIONS, REASONS FOR CAUTION: Strengths of the study include the large sample size and the broad set of potential confounders measured. However, results may have been underestimated due to survival bias. We cannot be sure about the sequence of the events in women with a late age at diabetes, as both events then occur in a short period. We could not distinguish between type 1 and type 2 diabetes.
WIDER IMPLICATIONS OF THE FINDINGS: Based on the literature, an accelerating effect of early-onset diabetes on ANM might be plausible. A delaying effect of late-onset diabetes on ANM has not been reported before, and is not in agreement with recent studies suggesting the opposite association.
STUDY FUNDING/COMPETING INTERESTS: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ) and Federal Ministry of Education and Research (BMMF) (Germany); Ministry of Health and Social Solidarity, Stavros Niarchos Foundation and Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia (no. 6236) and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and Västerbotten (Sweden); Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and Wellcome Trust (UK). None of the authors reported a conflict of interest.
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.