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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.

Key Points The International Agency for Research on Cancer has determined that, based on results from epidemiological studies, people who are overweight or obese are at increased risk of developing several cancer types, including adenocarcinoma of the oesophagus, colon cancer, breast cancer (in postmenopausal women), endometrial cancer and kidney (renal-cell) cancer. Epidemiological evidence also indicates that cancers of the liver, gallbladder and pancreas are obesity related, and that obesity might also increase risk for haematopoietic cancers and for aggressive prostate cancer. No association is seen between obesity and lung cancer. Results for other cancers have been inconsistent. Insulin resistance develops as a metabolic adaptation to increased levels of circulating free fatty acids released from adipose tissue, especially intra-abdominal adipose. Insulin resistance is generally compensated by increased pancreatic insulin secretion. There is mounting epidemiological and experimental evidence to indicate that chronic hyperinsulinaemia increases risk of cancers of the colon and endometrium, and probably other tumours (for example, of the pancreas and kidney). Serum levels of insulin-like growth factor 1 (IGF1) are also associated with different forms of cancer. However, there is no simple, direct relationship between circulating levels of IGF1 and the degree of adiposity. Circulating levels of oestrogens are strongly related to adiposity. For cancers of the breast (in postmenopausal women) and endometrium, the effects of overweight and obesity on cancer risk are largely mediated by increased oestrogen levels. In 4–8% of premenopausal women, obesity and ensuing insulin resistance can either cause or aggravate syndromes of ovarian androgen excess (polycystic ovary syndrome) and chronic progesterone deficiency. There is strong evidence that such syndromes, along with reduced progesterone production, increase the risk of endometrial cancer. Successful intervention strategies for weight loss and maintenance at the individual and community level are needed to reduce cancer risk. The prevalence of obesity is rapidly increasing globally. Epidemiological studies have associated obesity with a range of cancer types, although the mechanisms by which obesity induces or promotes tumorigenesis vary by cancer site. These include insulin resistance and resultant chronic hyperinsulinaemia, increased bioavailability of steroid hormones and localized inflammation. Gaining a better understanding of the relationship between obesity and cancer can provide new insight into mechanisms of cancer pathogenesis.

Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI < 18.5 kg/m 2 ) or obese (BMI ≥ 30 kg/m 2 ) categories, while the highest quartile of ABSI separated 18–39% of the individuals within each BMI category, which had 22–55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.

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.

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.

Background Circulating concentrations of lipid biomarkers are associated with risk of cardiovascular diseases (CVD). The evidence for a relationship with cancer risk, however, is not entirely consistent. This study aims to assess the relationships of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), apolipoprotein (a) (apo(a)), apoB-100, and lipoprotein(a) (Lp(a)) with risk of common cancer forms and total cancer mortality in comparison to incidence and mortality of CVD. Methods We selected a case-cohort sample out of the prospective EPIC–Heidelberg study, including a random subcohort ( n  = 2739), and cases of cancer ( n  = 1632), cancer mortality ( n  = 761), CVD ( n  = 1070), and CVD mortality ( n  = 381). Concentrations of lipid biomarkers were measured in pre-diagnostic blood samples. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Prentice-weighted Cox regression models. Results High levels of circulating apoB-100 and TG were inversely associated and high HDL-C levels were positively associated with breast cancer risk (highest vs. lowest quartile (Q4 vs. Q1), HR apoB 0.71, 95% CI 0.52–0.98; HR TG 0.65, 0.46–0.92; and HR HDL 1.39, 1.01–1.93). Higher levels of Lp(a) were associated with an increase in prostate cancer risk (Q4 vs. Q1, HR Lp(a) 1.43, 1.02–2.03) and high levels of apo(a) were associated with a decrease in lung cancer risk (Q4 vs. Q1, HR apo(a) 0.52, 0.30–0.91). High TC, HDL-C, apo(a), and Lp(a) levels were associated with a reduction in total cancer mortality (Q4 vs. Q1, HR TC 0.71, 0.54–0.94; HR HDL 0.67, 0.50–0.91; HR apo(a) 0.71, 0.54–0.93; and HR Lp(a) 0.74, 0.57–0.98). All lipid biomarkers were associated with risk of myocardial infarction, whereby TC, apoB-100, TG, and Lp(a) were positively and HLD-C and apo(a) inversely associated with risk. Only high levels of TG were associated with an increased risk of stroke. None of the lipids were associated with risk of colorectal cancer and with risk of CVD mortality after multivariable adjustments. Conclusions This prospective study demonstrates inverse associations of lipid biomarkers with cancer incidence and mortality, with the exception of positive associations of HDL-C and Lp(a) with breast and prostate cancer risk, respectively. Thus, the observed cancer risk pattern clearly differs from the CVD risk pattern.

Background Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. Methods In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. Results During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. Conclusion Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.

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.

Inclusion of clinical parameters limits the application of most cardiovascular disease (CVD) prediction models to clinical settings. We developed and externally validated a non-clinical CVD risk score with a clinical extension and compared the performance to established CVD risk scores. We derived the scores predicting CVD (non-fatal and fatal myocardial infarction and stroke) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 25,992, cases = 683) using competing risk models and externally validated in EPIC-Heidelberg (n = 23,529, cases = 692). Performance was assessed by C -indices, calibration plots, and expected-to-observed ratios and compared to a non-clinical model, the Pooled Cohort Equation, Framingham CVD Risk Scores (FRS), PROCAM scores, and the Systematic Coronary Risk Evaluation (SCORE). Our non-clinical score included age, gender, waist circumference, smoking, hypertension, type 2 diabetes, CVD family history, and dietary parameters. C -indices consistently indicated good discrimination (EPIC-Potsdam 0.786, EPIC-Heidelberg 0.762) comparable to established clinical scores (thereof highest, FRS: EPIC-Potsdam 0.781, EPIC-Heidelberg 0.764). Additional clinical parameters slightly improved discrimination (EPIC-Potsdam 0.796, EPIC-Heidelberg 0.769). Calibration plots indicated very good calibration with minor overestimation in the highest decile of predicted risk. The developed non-clinical 10-year CVD risk score shows comparable discrimination to established clinical scores, allowing assessment of individual CVD risk in physician-independent settings.