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Abstract Context The functional status of organs, such as the liver, involved in IGF-1 signaling pathways influences circulating levels of IGF-1 and hence its relationship to risk of chronic disease and mortality, yet this has received limited attention. Objective To examine the relationship between IGF-1 and risk of morbidity and mortality from cancer, cardiovascular diseases (CVD), and all causes, accounting for liver function. Methods This study was a case-cohort design nested within EPIC-Heidelberg. IGF-1 was measured in 7461 stored serum samples collected from 1994 to 1998. Median follow-up for incident mortality events was 17.5 years. The case-cohort included a subcohort of 1810 men and 1890 women, in addition to 1668 incident cases of cancer (623 breast, 577 prostate, 202 lung, and 268 colorectal), and 1428 cases of CVD (707 myocardial infarctions and 723 strokes) and 2441 cases of death. Results Higher IGF-1 levels showed direct associations with risks of breast (1.25; 95% CI [1.06-1.47]) and prostate (1.31; [1.09-1.57]) cancers. Restricted cubic splines plots and models including IGF-1 as quintiles revealed a U-shaped relationship between the biomarker and mortality. Participants with the lowest and the highest levels of IGF-1 experienced higher hazards of mortality from cancer, CVD, and all causes. The U-shaped form of the relationship persisted but was attenuated in analyses including only participants without any indications of liver dysfunction. Conclusion This large population-based prospective study showed that both individuals with lowest and highest levels of circulating IGF-1 were at increased risk of deaths from cancer, CVD, and all causes. For individuals with low IGF-1, the excess risks of death were more pronounced among individuals with liver cancer and cirrhosis but were also present among individuals without elevated liver enzymes.

Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI) in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre) was 0.75 (0.72-0.79) to 0.88 (0.84-0.92) for all-cause, 0.76 (0.69-0.83) to 0.84 (0.76-0.92) for CVD and 0.78 (0.73-0.83) to 0.91 (0.85-0.97) for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors.

Background: It has long been proposed that albumin, bilirubin and uric acid may inhibit cancer development due to their anti-oxidative properties. However, there is a lack of population-based studies on blood levels of these molecules and cancer risk. Methods: Associations between pre-diagnostic serum albumin, bilirubin and uric acid and the risks of common cancers as well as cancer death in the EPIC-Heidelberg cohort were evaluated by multivariable Cox regression analyses. A case–cohort sample including a random subcohort ( n =2739) and all incident cases of breast ( n =627), prostate ( n =554), colorectal ( n =256), and lung cancer ( n =195) as well as cancer death ( n =761) that occurred between baseline (1994–1998) and 2009 was used. Results: Albumin levels were inversely associated with breast cancer risk (hazard ratio Quartile 4 vs Quartile 1 (95% CI): 0.71 (0.51, 0.99), P linear trend =0.004) and overall cancer mortality (HR Q4 vs Q1 (95% CI): 0.64 (0.48, 0.86), P linear trend <0.001) after multivariable adjustment. Uric acid levels were also inversely associated with breast cancer risk (HR Q4 vs Q1 (95% CI): 0.72 (0.53, 0.99), P linear trend =0.043) and cancer mortality (HR Q4 vs Q1 (95% CI): 0.75 (0.58, 0.98), P linear trend =0.09). There were no significant associations between albumin or uric acid and prostate, lung and colorectal cancer. Serum bilirubin was not associated with any cancer end point. Conclusions: The present findings indicate that higher levels of albumin and uric acid are related to lower risks of breast cancer and cancer mortality. Further studies are needed to assess whether the observed associations are causal.

Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. 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. 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.

The number of prescribed medications might be used as proxy indicator for general health status, in models to predict mortality risk. To estimate the time-varying association between active pharmaceutical ingredient (API) count and all-cause mortality, we analyzed data from a population cohort in Heidelberg (Germany), including 25,546 participants with information on medication use collected at 3-yearly intervals from baseline recruitment (1994–1998) until end of 2014. A total of 4548 deaths were recorded until May 2019. Time-dependent modeling was used to estimate hazard ratios (HR) and their 95% confidence intervals (CI) for all-cause mortality in relation to number of APIs used, within three strata of age (≤ 60, > 60 to  ≤ 70 and > 70 years) and adjusting for lifestyle-related risk factors. For participants reporting commonly used APIs only (i.e., API types accounting for up to 80% of medication time in the population) total API counts showed no association with mortality risk within any age stratum. However, when at least one of the APIs was less common, the total API count showed a strong relationship with all-cause mortality especially up to age ≤ 60, with HR up to 3.70 (95% CI 2.30–5.94) with 5 or 6 medications and 8.19 (5.61–11.97) for 7 or more APIs (versus none). Between > 60 and 70 years of age this risk association was weaker, with HR up to 3.96 (3.14–4.98) for 7 or more APIs, and above 70 years it was weakened further (HR up to 1.54 (1.34–1.79)). Multiple API-use may predict mortality risk in middle-aged and women and men ≤ 70 years, but only if it includes at least one less frequently used API type. With advancing age, and multiple medication becomes increasingly prevalent, the association of API count with risk of death progressively attenuates, suggesting an increasing complexity with age of underlying mortality determinants.

Biological age is an important risk factor for chronic diseases. We examined the associations between five markers of unhealthy ageing; Growth Differentiation Factor-15 (GDF-15), N-terminal pro-brain natriuretic peptide (NT-proBNP), glycated hemoglobin A1c (HbA1C), C-Reactive Protein (CRP) and cystatin-C; with risks of cancer and cardiovascular disease (CVD). We used a case-cohort design embedded in the EPIC-Heidelberg cohort, including a subcohort of 3792 participants along with 4867 incident cases of cancer and CVD. Hazard ratios (HRs) were computed and the strongest associations were used to build weighted multi-marker combinations, and their associations with cancer and CVD risks were tested. After adjusting for common confounders, we observed direct associations of GDF-15 with lung cancer risk, NT-proBNP with breast, prostate and colorectal cancers, HbA1C with lung, colorectal, and breast cancer risks, and CRP with lung and colorectal cancer risks. An inverse association was observed for GDF-15 and prostate cancer risk. We also found direct associations of all 5 markers with myocardial infarction (MI) risk, and of GDF-15, NT-proBNP, CRP and cystatin-C with stroke risk. A combination of the independently-associated markers showed a moderately strong association with the risks of cancer and CVD (HR Q4-Q1 ranged from 1.78 [1.36, 2.34] for breast cancer, when combining NT-proBNP and HbA1C, to 2.87 [2.15, 3.83] for MI when combining NT-proBNP, HbA1C, CRP and cystatin-C). This analysis suggests that combinations of biomarkers related to unhealthy ageing show strong associations with cancer risk, and corroborates published evidence on CVD risk. If confirmed in other studies, using these biomarkers could be useful for the identification of individuals at higher risk of age-related diseases.

ObjectivesElevated liver enzyme concentrations in blood are indicative of liver diseases and may provide an early signal for being at risk for other chronic diseases. Our study aimed to assess the relationships of alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), alanine aminotransferase (ALT), aspartate transaminase (AST) and the De Ritis ratio (AST/ALT) with incidence and mortality of cardiovascular diseases (CVD) and the four most common cancers, that is, breast, prostate, colorectal and lung.Setting, participants and outcome measuresWe analysed a case-cohort sample of the prospective European Prospective Investigation into Cancer and Nutrition-Heidelberg cohort, including cancer (n=1632), cancer mortality (n=761), CVD (n=1070), CVD mortality (n=381) and a random subcohort (n=2739) with an average follow-up duration of 15.6 years. Concentrations of liver enzymes were measured in prediagnostic blood samples and Prentice-weighted Cox regression models were used to estimate HRs with 95% CIs.ResultsHigh ALP levels were associated with increased risk for lung cancer and all-cause mortality (highest vs lowest quartile, multivariable adjusted HR=2.39 (95% CI 1.30 to 4.39), HR=1.31 (95% CI 1.02 to 1.67)), high AST levels with all-cause mortality (HR=1.45 (95% CI 1.15 to 1.82)), and a high De Ritis ratio with prostate cancer risk, all-cause and cancer mortality (HR=1.61 (95% CI 1.10 to 2.36), HR=1.60 (95% CI 1.25 to 2.04), HR=1.67 (95% CI 1.26 to 2.23)). Using cut-points for liver enzyme levels above normal, we observed positive associations for all-cause mortality with ALP, GGT and AST, and assigning a combined risk score resulted in positive associations with all-cause and cause-specific mortality.ConclusionsMeasurements of serum liver enzymes, as routinely performed in health check-ups, may support the identification of individuals at increased risk for all-cause mortality. Further prospective studies are needed to verify our first results on individual cancers and on a combined risk score.

Specific nutrients or foods have been inconsistently associated with ulcerative colitis (UC) or Crohn's disease (CD) risks. Thus, we investigated associations between diet as a whole, as dietary patterns, and UC and CD risks.MethodsWithin the prospective EPIC (European Prospective Investigation into Cancer) study, we set up a nested matched case–control study among 366,351 participants with inflammatory bowel disease data, including 256 incident cases of UC and 117 of CD, and 4 matched controls per case. Dietary intake was recorded at baseline from validated food frequency questionnaires. Incidence rate ratios of developing UC and CD were calculated for quintiles of the Mediterranean diet score and a posteriori dietary patterns produced by factor analysis.ResultsNo dietary pattern was associated with either UC or CD risks. However, when excluding cases occurring within the first 2 years after dietary assessment, there was a positive association between a “high sugar and soft drinks” pattern and UC risk (incidence rate ratios for the fifth versus first quintile, 1.68 [1.00–2.82]; Ptrend = 0.02). When considering the foods most associated with the pattern, high consumers of sugar and soft drinks were at higher UC risk only if they had low vegetables intakes.ConclusionsA diet imbalance with high consumption of sugar and soft drinks and low consumption of vegetables was associated with UC risk. Further studies are needed to investigate whether microbiota alterations or other mechanisms mediate this association.

BackgroundCA125 is the best available yet insufficiently sensitive biomarker for early detection of ovarian cancer. There is a need to identify novel biomarkers, which individually or in combination with CA125 can achieve adequate sensitivity and specificity for the detection of earlier-stage ovarian cancer.MethodsIn the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we measured serum levels of 92 preselected proteins for 91 women who had blood sampled ≤18 months prior to ovarian cancer diagnosis, and 182 matched controls. We evaluated the discriminatory performance of the proteins as potential early diagnostic biomarkers of ovarian cancer.ResultsNine of the 92 markers; CA125, HE4, FOLR1, KLK11, WISP1, MDK, CXCL13, MSLN and ADAM8 showed an area under the ROC curve (AUC) of ≥0.70 for discriminating between women diagnosed with ovarian cancer and women who remained cancer-free. All, except ADAM8, had shown at least equal discrimination in previous case-control comparisons. The discrimination of the biomarkers, however, was low for the lag-time of >9–18 months and paired combinations of CA125 with any of the 8 markers did not improve discrimination compared to CA125 alone.ConclusionUsing pre-diagnostic serum samples, this study identified markers with good discrimination for the lag-time of 0–9 months. However, the discrimination was low in blood samples collected more than 9 months prior to diagnosis, and none of the markers showed major improvement in discrimination when added to CA125.

BackgroundDietary pattern analysis has gained particular interest, because it reflects the complexity of dietary intake. The aim of this study was to explore the associations between a posteriori dietary patterns, derived using a data-driven approach, and the risk of differentiated thyroid cancer (TC) in Europe.MethodsThis investigation included 450,064 adults from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Dietary intake was assessed using validated country-specific dietary questionnaires. A posteriori dietary patterns were computed using principal component analyses. Cox regression was used to calculate multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsAfter a mean follow-up time of 14 years, 712 first differentiated TCs were diagnosed. In the fully adjusted model, a dietary pattern characterized by alcohol consumption (basically beer and wine) was negatively associated with differentiated TC risk (HRQ4vs.Q1 = 0.75; 95% CI:0.60–0.94, P-trend = 0.005), while a dietary pattern rich in sweetened beverages was positively associated with differentiated TC risk (HRQ4vs.Q1 = 1.26; 95% CI:0.99–1.61; P-trend = 0.07). The remaining 8 dietary patterns were not related to differentiated TC risk. The intake of sweetened beverages was positively associated with differentiated TC risk (HR100mL/d = 1.05; 95% CI:1.00–1.11), especially with papillary TC risk (HR100mL/d = 1.07; 95% CI:1.01–1.13). Similar results were observed with sugary and artificially sweetened beverages.ConclusionsThe investigation of dietary patterns detected that the consumption of sweetened beverages was associated with a higher risk of differentiated thyroid cancer. Our results are in line with the general dietary recommendations of reducing the consumption of sweetened beverages.