Giovanna Tagliabue

OBJECTIVES: To assess international trends and patterns of prenatal diagnosis of critical congenital heart defects (CCHDs) and their relation to total and live birth CCHD prevalence and mortality. SETTING: Fifteen birth defect surveillance programmes that participate in the International Clearinghouse for Birth Defects Surveillance and Research from 12 countries in Europe, North and South America and Asia. PARTICIPANTS: Live births, stillbirths and elective terminations of pregnancy for fetal anomaly diagnosed with 1 of 12 selected CCHD, ascertained by the 15 programmes for delivery years 2000 to 2014. RESULTS: 18 243 CCHD cases were reported among 8 847 081 births. The median total prevalence was 19.1 per 10 000 births but varied threefold between programmes from 10.1 to 31.0 per 10 000. CCHD were prenatally detected for at least 50% of the cases in one-third of the programmes. However, prenatal detection varied from 13% in Slovak Republic to 87% in some areas in France. Prenatal detection was consistently high for hypoplastic left heart syndrome (64% overall) and was lowest for total anomalous pulmonary venous return (28% overall). Surveillance programmes in countries that do not legally permit terminations of pregnancy tended to have higher live birth prevalence of CCHD. Most programmes showed an increasing trend in prenatally diagnosed CCHD cases. DISCUSSION AND CONCLUSIONS: Prenatal detection already accounts for 50% or more of CCHD detected in many programmes and is increasing. Local policies and access likely account for the wide variability of reported occurrence and prenatal diagnosis. Detection rates are high especially for CCHD that are more easily diagnosed on a standard obstetric four-chamber ultrasound or for fetuses that have extracardiac anomalies. These ongoing trends in prenatal diagnosis, potentially in combination with newborn pulse oximetry, are likely to modify the epidemiology and clinical outcomes of CCHD in the near future.

OBJECTIVE: To examine the association between serum concentrations of total cholesterol, high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol, triglycerides, apolipoprotein A-I (apoA), apolipoprotein B and the incidence of colorectal cancer (CRC). DESIGN: Nested case-control study. SETTING: The study was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC), a cohort of more than 520,000 participants from 10 western European countries. PARTICIPANTS: 1238 cases of incident CRC, which developed after enrolment into the cohort, were matched with 1238 controls for age, sex, centre, follow-up time, time of blood collection and fasting status. MAIN OUTCOME MEASURES: Serum concentrations were quantitatively determined by colorimetric and turbidimetric methods. Dietary and lifestyle data were obtained from questionnaires. Conditional logistic regression models were used to estimate incidence rate ratios (RRs) and 95% CIs which were adjusted for height, weight, smoking habits, physical activity, education, consumption of fruit, vegetables, meat, fish, alcohol, fibre and energy. RESULTS: After adjustments, the concentrations of HDL and apoA were inversely associated with the risk of colon cancer (RR for 1 SD increase of 16.6 mg/dl in HDL and 32.0 mg/dl in apoA of 0.78 (95% CI 0.68 to 0.89) and 0.82 (95% CI 0.72 to 0.94), respectively). No association was observed with the risk of rectal cancer. Additional adjustment for biomarkers of systemic inflammation, insulin resistance and oxidative stress or exclusion of the first 2 years of follow-up did not influence the association between HDL and risk of colon cancer. CONCLUSIONS: These findings show that high concentrations of serum HDL are associated with a decreased risk of colon cancer. The mechanism behind this association needs further elucidation.

We examined consumption of animal foods, protein and calcium in relation to risk of prostate cancer among 142 251 men in the European Prospective Investigation into Cancer and Nutrition. Associations were examined using Cox regression, stratified by recruitment centre and adjusted for height, weight, education, marital status and energy intake. After an average of 8.7 years of follow-up, there were 2727 incident cases of prostate cancer, of which 1131 were known to be localised and 541 advanced-stage disease. A high intake of dairy protein was associated with an increased risk, with a hazard ratio for the top versus the bottom fifth of intake of 1.22 (95% confidence interval (CI): 1.07-1.41, P(trend)=0.02). After calibration to allow for measurement error, we estimated that a 35-g day(-1) increase in consumption of dairy protein was associated with an increase in the risk of prostate cancer of 32% (95% CI: 1-72%, P(trend)=0.04). Calcium from dairy products was also positively associated with risk, but not calcium from other foods. The results support the hypothesis that a high intake of protein or calcium from dairy products may increase the risk for prostate cancer.

BACKGROUND: The comparative performance of existing models for prediction of type 2 diabetes across populations has not been investigated. We validated existing non-laboratory-based models and assessed variability in predictive performance in European populations. METHODS: We selected non-invasive prediction models for incident diabetes developed in populations of European ancestry and validated them using data from the EPIC-InterAct case-cohort sample (27,779 individuals from eight European countries, of whom 12,403 had incident diabetes). We assessed model discrimination and calibration for the first 10 years of follow-up. The models were first adjusted to the country-specific diabetes incidence. We did the main analyses for each country and for subgroups defined by sex, age (<60 years vs ≥60 years), BMI (<25 kg/m(2)vs ≥25 kg/m(2)), and waist circumference (men <102 cm vs ≥102 cm; women <88 cm vs ≥88 cm). FINDINGS: We validated 12 prediction models. Discrimination was acceptable to good: C statistics ranged from 0·76 (95% CI 0·72-0·80) to 0·81 (0·77-0·84) overall, from 0·73 (0·70-0·76) to 0·79 (0·74-0·83) in men, and from 0·78 (0·74-0·82) to 0·81 (0·80-0·82) in women. We noted significant heterogeneity in discrimination (pheterogeneity<0·0001) in all but one model. Calibration was good for most models, and consistent across countries (pheterogeneity>0·05) except for three models. However, two models overestimated risk, DPoRT by 34% (95% CI 29-39%) and Cambridge by 40% (28-52%). Discrimination was always better in individuals younger than 60 years or with a low waist circumference than in those aged at least 60 years or with a large waist circumference. Patterns were inconsistent for BMI. All models overestimated risks for individuals with a BMI of <25 kg/m(2). Calibration patterns were inconsistent for age and waist-circumference subgroups. INTERPRETATION: Existing diabetes prediction models can be used to identify individuals at high risk of type 2 diabetes in the general population. However, the performance of each model varies with country, age, sex, and adiposity. FUNDING: The European Union.