Giovanni Veronesi

Twenty-five-year trends in myocardial infarction attack and mortality rates, and case-fatality, in six European populations

Objective Due to the burden of coronary heart disease (CHD), the monitoring of CHD trends is required. This study sought to examine the acute myocardial infarction (AMI) trends in attack and mortality rates, and in 28-day case-fatality, in six European populations during 1985–2010. Methods Data consisted of 78 128 AMI events included in eight population-based registries from Finland (several populations), Italy (Brianza and Varese), Germany (Augsburg), France (Haute-Garonne), Spain (Girona) and Estonia (Tallinn). AMI event rates and case-fatality trends were analysed using the annual percentage change (APC) obtained by negative binomial and joinpoint regression. Results AMI attack and mortality rates decreased in most populations. Finland experienced the steepest decline in attack rates (APC=−4.4% (95% CI −5.1 to −2.9) in men; −4.0% (−5.1 to −2.8), in women). Total-hospital and inhospital case-fatality decreased in all populations except in Tallinn. The steepest decline in total case-fatality occurred in Spain (−3.8% (−5.3 to −2.4) in men; −5.1% (−6.9 to −3.3) in women). Prehospital case-fatality trends differed significantly by population and sex. The trends for all included populations showed a significant decline in AMI event rates and case-fatality, in both sexes and all age groups. However, in women aged 65–74 years, a significant increase in total case-fatality occurred in 2005–2010 (4.7% (0.7 to 8.8)). Conclusions AMI event rates and inhospital case-fatality declined in 1985–2010 in almost all populations analysed. Prehospital case-fatality declined only in certain population groups, showing differences by sex. These results highlight the need of specific strategies in AMI prevention for certain groups and populations.

Prevalence and risk factors of human papillomavirus infection by penile site in uncircumcised Kenyan men

Human papillomavirus (HPV) prevalence was estimated from 2,705 sexually active, uncircumcised, human immunodeficiency virus seronegative men aged 17–28 years in Kisumu, Kenya. HPV prevalence was 51.1% (95% confidence interval: 49.2–53.0%) in penile cells from the glans/coronal sulcus and/or shaft. HPV prevalence varied by anatomical site, with 46.5% positivity in the glans/coronal sulcus compared with 19.1% in the shaft (p < 0.0001). High‐risk HPV was detected in 31.2% of glans and 12.3% of shaft samples (p < 0.0001). HPV16 was the most common type and 29.2% of men were infected with more than one HPV type. Risk factors for HPV infection included presence of C. trachomatis, N. gonorrhea, self‐reported sexually transmitted infections, and less frequent bathing. Lifetime number of sexual partners and herpes simplex virus type‐2 seropositivity were also marginally associated with HPV infection.

Age- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10−107) and stratified analyses (all P < 3.3 × 10−30). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.

Impact of treatment on survival in polymyositis and dermatomyositis. A single-centre long-term follow-up study

OBJECTIVE To assess the long-term outcome in polymyositis (PM) and dermatomyositis (DM), with a particular emphasis on mortality and influence of treatment. METHODS Diagnosis was based according to the Bohan and Peters criteria. Patients have been followed up by a standardised protocol. Deaths were registered and causes of death were ascertained. Survival probability at 5 and 10years was estimated according to the Kaplan-Meier method, in the overall series and by a diagnostic group and an initial treatment. Mortality hazard ratios (95% CI) for major clinical and demographic features were estimated through univariate and multivariate Cox proportional hazard models. RESULTS 91 patients (43 PM and 48 DM) were available for the study. Baseline characteristics were not different from those previously reported. Twenty-two patients (24%) died after a median follow-up of 8.7years. As for idiopathic myositis, the survival probabilities at 5 and 10years from the diagnosis were 96.2% and 88.8% for PM respectively; and 93.9% for DM, whereas a higher mortality was documented for cancer-associated myositis and overlap myositis. Male sex [HR=2.4, 95% CI 1.0 to 5.6], heart involvement (HR=1.8), interstitial lung disease (HR=2.3) and arthritis (HR=1.8) increased the risk of mortality, these risk excesses were confirmed in the multivariate analysis. Independent of these features, a higher mortality was documented for patients treated with glucocorticoids (HR=2.3) or immunosuppressants (HR=2.1) when compared to patients treated with immunoglobulins. CONCLUSION Our study, with longitudinal and statistical analyses, suggests that survival has considerably increased in patients with PM/DM. Prognostic factors for mortality are male sex, and heart and lung involvement. Immunoglobulin treatment, intravenously or subcutaneously, is associated with a better survival.

Gender differences in the association between education and the incidence of cardiovascular events in Northern Italy

BACKGROUND The educational differences in the incidence of major cardiovascular events are under-studied in Southern Europe and among women. METHODS The study sample includes n = 5084 participants to 4 population-based Northern Italian cohorts, aged 35-74 at baseline and with no previous cardiovascular events. The follow-up to ascertain the first onset of coronary heart disease (CHD) or ischaemic stroke ended in 2002. At baseline, major cardiovascular risk factors were investigated adopting the standardized MONICA procedures. Two educational classes were obtained from years of schooling. Age- and risk factors-adjusted hazard ratios of first CHD or ischaemic stroke were estimated through sex-specific separate Cox models (high education as reference). RESULTS Median follow-up time was 12 years. Event rates were 6.38 (CHD) and 2.12 (ischaemic stroke) per 1000 person-years in men; and 1.59 and 0.94 in women. In men, low education was associated with higher mean Body Mass Index and prevalence of diabetes and cigarette smokers; but also with higher HDL cholesterol and a more favourable alcohol intake pattern. Less-educated women had higher mean systolic blood pressure, Body Mass Index and HDL cholesterol and were more likely to have diabetes. Men and women in the low educational class had a 2-fold increase in ischaemic stroke and CHD incidence, respectively, after controlling for major risk factors. Education was not associated with CHD incidence in men. Higher ischaemic stroke rates were observed among more educated women. CONCLUSION In this northern Italian population, the association between education and cardiovascular risk seems to vary by gender.

Lipoprotein(a) and the risk of cardiovascular disease in the European population: results from the BiomarCaRE consortium

Abstract Aims As promising compounds to lower Lipoprotein(a) (Lp(a)) are emerging, the need for a precise characterization and comparability of the Lp(a)-associated cardiovascular risk is increasing. Therefore, we aimed to evaluate the distribution of Lp(a) concentrations across the European population, to characterize the association with cardiovascular outcomes and to provide high comparability of the Lp(a)-associated cardiovascular risk by use of centrally determined Lp(a) concentrations. Methods and results Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE)-project, we analysed data of 56 804 participants from 7 prospective population-based cohorts across Europe with a maximum follow-up of 24 years. All Lp(a) measurements were performed in the central BiomarCaRE laboratory (Biokit Quantia Lp(a)-Test; Abbott Diagnostics). The three endpoints considered were incident major coronary events (MCE), incident cardiovascular disease (CVD) events, and total mortality. We found lower Lp(a) levels in Northern European cohorts (median 4.9 mg/dL) compared to central (median 7.9 mg/dL) and Southern European cohorts (10.9 mg/dL) (Jonckheere–Terpstra test P < 0.001). Kaplan–Meier curves showed the highest event rate of MCE and CVD events for Lp(a) levels ≥90th percentile (log-rank test: P < 0.001 for MCE and CVD). Cox regression models adjusted for age, sex, and cardiovascular risk factors revealed a significant association of Lp(a) levels with MCE and CVD with a hazard ratio (HR) of 1.30 for MCE [95% confidence interval (CI) 1.15‒1.46] and of 1.25 for CVD (95% CI 1.12‒1.39) for Lp(a) levels in the 67‒89th percentile and a HR of 1.49 for MCE (95% CI 1.29‒1.73) and of 1.44 for CVD (95% CI 1.25‒1.65) for Lp(a) levels ≥ 90th percentile vs. Lp(a) levels in the lowest third (P < 0.001 for all). There was no significant association between Lp(a) levels and total mortality. Subgroup analysis for a continuous version of cube root transformed Lp(a) identified the highest Lp(a)-associated risk in individuals with diabetes [HR for MCE 1.31 (95% CI 1.15‒1.50)] and for CVD 1.22 (95% CI 1.08‒1.38) compared to those without diabetes [HR for MCE 1.15 (95% CI 1.08‒1.21; HR for CVD 1.13 (1.07–1.19)] while no difference of the Lp(a)- associated risk were seen for other cardiovascular high risk states. The addition of Lp(a) levels to a prognostic model for MCE and CVD revealed only a marginal but significant C-index discrimination measure increase (0.001 for MCE and CVD; P < 0.05) and net reclassification improvement (0.010 for MCE and 0.011 for CVD). Conclusion In this large dataset on harmonized Lp(a) determination, we observed regional differences within the European population. Elevated Lp(a) was robustly associated with an increased risk for MCE and CVD in particular among individuals with diabetes. These results may lead to better identification of target populations who might benefit from future Lp(a)-lowering therapies.

Smoking and All-cause Mortality in Older Adults: Results From the CHANCES Consortium

INTRODUCTION Smoking is known to be a major cause of death among middle-aged adults, but evidence on its impact and the benefits of smoking cessation among older adults has remained limited. Therefore, we aimed to estimate the influence of smoking and smoking cessation on all-cause mortality in people aged ≥60 years. METHODS Relative mortality and mortality rate advancement periods (RAPs) were estimated by Cox proportional hazards models for the population-based prospective cohort studies from Europe and the U.S. (CHANCES [Consortium on Health and Ageing: Network of Cohorts in Europe and the U.S.]), and subsequently pooled by individual participant meta-analysis. Statistical analyses were performed from June 2013 to March 2014. RESULTS A total of 489,056 participants aged ≥60 years at baseline from 22 population-based cohort studies were included. Overall, 99,298 deaths were recorded. Current smokers had 2-fold and former smokers had 1.3-fold increased mortality compared with never smokers. These increases in mortality translated to RAPs of 6.4 (95% CI=4.8, 7.9) and 2.4 (95% CI=1.5, 3.4) years, respectively. A clear positive dose-response relationship was observed between number of currently smoked cigarettes and mortality. For former smokers, excess mortality and RAPs decreased with time since cessation, with RAPs of 3.9 (95% CI=3.0, 4.7), 2.7 (95% CI=1.8, 3.6), and 0.7 (95% CI=0.2, 1.1) for those who had quit <10, 10 to 19, and ≥20 years ago, respectively. CONCLUSIONS Smoking remains as a strong risk factor for premature mortality in older individuals and cessation remains beneficial even at advanced ages. Efforts to support smoking abstinence at all ages should be a public health priority.

Education and coronary heart disease: mendelian randomisation study

Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10−8). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits.

Educational class inequalities in the incidence of coronary heart disease in Europe

Objective To estimate the burden of social inequalities in coronary heart disease (CHD) and to identify their major determinants in 15 European populations. Methods The MORGAM (MOnica Risk, Genetics, Archiving and Monograph) study comprised 49 cohorts of middle-aged European adults free of CHD (110 928 individuals) recruited mostly in the mid-1980s and 1990s, with comparable assessment of baseline risk and follow-up procedures. We derived three educational classes accounting for birth cohorts and used regression-based inequality measures of absolute differences in CHD rates and HRs (ie, Relative Index of Inequality, RII) for the least versus the most educated individuals. Results N=6522 first CHD events occurred during a median follow-up of 12 years. Educational class inequalities accounted for 343 and 170 additional CHD events per 100 000 person-years in the least educated men and women compared with the most educated, respectively. These figures corresponded to 48% and 71% of the average event rates in each gender group. Inequalities in CHD mortality were mainly driven by incidence in the Nordic countries, Scotland and Lithuania, and by 28-day case-fatality in the remaining central/South European populations. The pooled RIIs were 1.6 (95% CI 1.4 to 1.8) in men and 2.0 (1.7 to 2.4) in women, consistently across population. Risk factors accounted for a third of inequalities in CHD incidence; smoking was the major mediator in men, and High-Density-Lipoprotein (HDL) cholesterol in women. Conclusions Social inequalities in CHD are still widespread in Europe. Since the major determinants of inequalities followed geographical and gender-specific patterns, European-level interventions should be tailored across different European regions.

The contribution of major risk factors and job strain to occupational class differences in coronary heart disease incidence: the MONICA Brianza and PAMELA population-based cohorts

Objectives We investigated the contribution of major coronary heart disease (CHD) risk factors and job strain to occupational class differences in CHD incidence in a pooled-cohort prospective study in northern Italy. Methods 2964 men aged 25–74 from four northern Italian population-based cohorts were investigated at baseline and followed for first fatal or non-fatal CHD event (171 events). Standardised procedures were used for baseline risk factor measurements, follow-up and validation of CHD events. Four occupational classes were derived from the Erikson–Goldthorpe–Portocarero social class scheme: higher and lower professionals and administrators, non-manual workers, skilled and unskilled manual workers, and the self-employed. HRs were estimated with Cox models. Results Among CHD-free subjects, with non-manual workers as the reference group, age-adjusted excess risks were found for professionals and administrators (+84%, p=0.02), the self-employed (+72%, p=0.04) and manual workers (+63%, p=0.04). The relationship was consistent across different CHD diagnostic categories. Adjusting for major risk factors only slightly reduced the reported excess risks. In a sub-sample of currently employed subjects, adjusting for major risk factors, sport physical activity and job strain reduced the excess risk for manual workers (relative change = −71.4%) but did not substantially modify the excess risks of professionals and administrators and the self-employed. Conclusions In our study, we found higher CHD incidence rates for manual workers, professionals and administrators, and the self-employed, compared to non-manual workers. When the entire spectrum of job categories is considered, the job strain model helped explain the CHD excess risk for manual workers but not for other occupational classes.