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Purpose Breast cancer incidence and survival is high, which results in high prevalence of breast cancer survivors. The risk of (death from) cardiovascular disease (CVD) is higher in patients exposed to cardiotoxic treatments, in particular if they have pre-existing CVD risk factors. This study systematically summarized the risk of death from CVD following breast cancer. Methods Databases of Medline, Embase, and the Cochrane Library were systematically searched using the following terms and synonyms: breast cancer, cardiovascular disease, and cause of death. Articles reporting on both risk and risk factors of CVD mortality following breast cancer were eligible for inclusion. The methodological quality of each article was assessed using the Newcastle Ottawa quality assessment scale for cohort studies. Results Fourteen articles were included assessing the risk of CVD mortality among 1,217,910 women with breast cancer. The methodological quality was high for the majority of the studies. Studies were heterogeneous in design, study population, length of follow-up, CVD outcomes, and risk factors. 1.6–10.4% of all women with breast cancer died of CVD. Women with breast cancer had a higher risk of CVD mortality than women from the general population. The risk of CVD mortality was higher among women with breast cancer with older age at diagnosis, left-sided tumor, diagnosis in an earlier calendar period, and black ethnic origin. Conclusions CVD is an important cause of death following breast cancer. Identification of patients at high risk of CVD is important to optimize CVD prevention and tailor breast cancer treatment.

Aims/hypothesis The relationship between cognitive function, cardiovascular disease and premature death is not well established in patients with type 2 diabetes. We assessed the effects of cognitive function in 11,140 patients with type 2 diabetes who participated in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial. Furthermore, we tested whether level of cognitive function altered the beneficial effects of the BP-lowering and glycaemic-control regimens in the trial. Methods Cognitive function was assessed using the Mini Mental State Examination at baseline, and defined by scores 28-30 (‘normal', n = 8,689), 24-27 (‘mild dysfunction', n = 2,231) and <24 (‘severe dysfunction', n = 212). Risks of major cardiovascular events, death and hypoglycaemia and interactions with treatment were assessed using Cox proportional hazards analysis. Results Relative to normal function, both mild and severe cognitive dysfunction significantly increased the multiple-adjusted risks of major cardiovascular events (HR 1.27, 95% CI 1.11-1.46 and 1.42, 95% CI 1.01-1.99; both p < 0.05), cardiovascular death (1.41, 95% CI 1.16-1.71 and 1.56, 95% CI 0.99-2.46; both p ≤ 0.05) and all-cause death (1.33, 95% CI 1.16-1.54 and 1.50, 95% CI 1.06-2.12; both p < 0.03). Severe, but not mild, cognitive dysfunction increased the risk of severe hypoglycaemia (HR 2.10, 95% CI 1.14-3.87; p = 0.018). There was no evidence of heterogeneity of treatment effects on cardiovascular outcomes in subgroups defined by cognitive function at baseline. Conclusions/interpretation Cognitive dysfunction is an independent predictor of clinical outcomes in patients with type 2 diabetes, but does not modify the effects of BP lowering or glucose control on the risks of major cardiovascular events. Trial registration: ClinicalTrials.gov NCT00145925 Funding: Supported by grants from Servier and from the National Health and Medical Research Council of Australia.

Multiple non-invasive tests are performed to diagnose coronary artery disease (CAD), but all are limited to either anatomical or functional assessments. Computed tomography derived Fractional Flow Reserve (CT-FFR) based on patient-specific lumped parameter models is a new test combining both characteristics simulating invasive FFR. This study aims to evaluate the added value of CT-FFR over other non-invasive tests to diagnose CAD. Patients with clinical suspicion of angina pectoris between 2010 and 2011 were included in this cross-sectional study. All underwent stress electrocardiography (X-ECG), SPECT, CT coronary angiography (CCTA) and CT-FFR. Invasive coronary angiography (ICA) and FFR were used as reference standard. Five models mimicking the clinical workflow were fitted and the area under receiver operating characteristic (AUROC) curve was used for comparison. 44% of the patients included in the analysis had a FFR of ≤ 0.80. The basic model including pre-test-likelihood and X-ECG had an AUROC of 0.79. The SPECT-strategy had an AUROC of 0.90 (p = 0.008), CCTA-strategy of 0.88 (p < 0.001), 0.93 when adding CT-FFR (p = 0.40) compared to 0.94 when combining CCTA and SPECT. This study shows adding on-site CT-FFR based on patient-specific lumped parameter models leads to an increased AUROC compared to the basic model. It improves the diagnostic work-up beyond SPECT or CCTA and is non-inferior to the combined strategy of SPECT and CCTA in the diagnosis of hemodynamically relevant CAD.

Aims/hypothesis The aim of the present study was to investigate the effect of blood pressure lowering and intensive glucose control on the incidence and progression of retinopathy in type 2 diabetic patients. Methods The Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation (ADVANCE) Retinal Measurements study, a substudy of ADVANCE, is a randomised (using a central, computer-based procedure) controlled 2 x 2 factorial trial comprising a double-blind comparison of blood pressure lowering with perindopril-indapamide vs placebo, and an open comparison of standard vs intensive glucose control targeting a HbA₁c of <= 6.5% in 1,602 diabetic patients from ADVANCE centres with access to retinal cameras conducted from 2001 to 2008. At baseline and the final visit, seven-field stereoscopic retinal photographs were taken and graded by blinded readers (gradeable baseline and final photographs from 1,241 patients). Progression of >=2 steps in the Early Treatment of Diabetic Retinopathy Study classification (using the eye with worst grading) was the primary outcome. Results Retinopathy progressed in 59 (4.8%) patients and developed in 128 (10.3%) patients over 4.1 years. Fewer patients on blood pressure-lowering treatment (n = 623) experienced incidence or progression of retinopathy compared with patients on placebo (n = 618), but the difference was not significant (OR 0.78; 95% CI 0.57-1.06; p = 0.12). Blood pressure-lowering treatment reduced the occurrence of macular oedema (OR 0.50; 95% CI 0.29-0.88; p = 0.016) and arteriovenous nicking compared with placebo (OR 0.60; 95% CI 0.38-0.94; p = 0.025). Compared with standard glucose control (n = 611), intensive glucose control (n = 630) did not reduce (p = 0.27) the incidence and progression of retinopathy (OR 0.84; 95% CI 0.61-1.15). Lower, borderline significant risks of microaneurysms, hard exudates and macular oedema were observed with intensive glucose control, adjusted for baseline retinal haemorrhages. These effects of the two treatments were independent and additive. Adverse events in the ADVANCE study are reported elsewhere. Conclusions/interpretation Blood pressure lowering or intensive glucose control did not significantly reduce the incidence and progression of retinopathy, although consistent trends towards a benefit were observed, with significant reductions in some lesions observed with both interventions. Trial registration: ClinicalTrials.gov ID no. NCT00145925. Funding: Grants from Servier and the National Health and Medical Research Council of Australia

Ideally, clinical prediction models are generalizable to other patient groups. Unfortunately, they perform regularly worse when validated in new patients and are then often redeveloped. While the original prediction model usually has been developed on a large data set, redevelopment then often occurs on the smaller validation set. Recently, methods to update existing prediction models with the data of new patients have been proposed. We used an existing model that preoperatively predicts the risk of severe postoperative pain (SPP) to compare five updating methods. The model was tested and updated with a set of 752 new patients (274 [36] with SPP). We studied the discrimination (ability to distinguish between patients with and without SPP) and calibration (agreement between the predicted risks and observed frequencies of SPP) of the five updated models in 283 other patients (100 [35%] with SPP). Simple recalibration methods improved the calibration to a similar extent as revision methods that made more extensive adjustments to the original model. Discrimination could not be improved by any of the methods. When the performance is poor in new patients, updating methods can be applied to adjust the model, rather than to develop a new model.

Prediction models tend to perform better on data on which the model was constructed than on new data. This difference in performance is an indication of the optimism in the apparent performance in the derivation set. For internal model validation, bootstrapping methods are recommended to provide biascorrected estimates of model performance. Results are often accepted without sufficient regard to the importance of external validation. This report illustrates the limitations of internal validation to determine generalizability of a diagnostic prediction model to future settings. A prediction model for the presence of serious bacterial infections in children with fever without source was derived and validated internally using bootstrap resampling techniques. Subsequently, the model was validated externally. In the derivation set (n=376), nine predictors were identified. The apparent area under the receiver operating characteristic curve (95% confidence interval) of the model was 0.83 (0.78–0.87) and 0.76 (0.67–0.85) after bootstrap correction. In the validation set (n=179) the performance was 0.57 (0.47–0.67). For relatively small data sets, internal validation of prediction models by bootstrap techniques may not be sufficient and indicative for the model's performance in future patients. External validation is essential before implementing prediction models in clinical practice.

Current guidelines barely support marine omega‑3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in cardiology, mainly because results of large trials were equivocal. Most large trials have tested EPA alone or EPA + DHA combined as a drug, thereby disregarding the relevance of their blood levels. These levels are frequently assessed with the Omega‑3 Index (percentage of EPA + DHA in erythrocytes), which is determined using a specific standardised analytical procedure. EPA and DHA are present in every human being at unpredictable levels (even in the absence of intake), and their bioavailability is complex. Both facts need to be incorporated into trial design and should direct clinical use of EPA and DHA. An Omega‑3 Index in the target range of 8–11% is associated with lower total mortality, fewer major adverse cardiac and other cardiovascular events. Moreover, functions of organs such as the brain benefit from an Omega‑3 Index in the target range, while untoward effects, such as bleeding or atrial fibrillation, are minimised. In pertinent intervention trials, several organ functions were improved, with improvements correlating with the Omega‑3 Index. Thus, the Omega‑3 Index is relevant in trial design and clinical medicine, which calls for a widely available standardised analytical procedure and a discussion on possible reimbursement of this test.

Blood pressure is an important determinant of the risks of macrovascular and microvascular complications of type 2 diabetes, and guidelines recommend intensive lowering of blood pressure for diabetic patients with hypertension. We assessed the effects of the routine administration of an angiotensin converting enzyme (ACE) inhibitor-diuretic combination on serious vascular events in patients with diabetes, irrespective of initial blood pressure levels or the use of other blood pressure lowering drugs. The trial was done by 215 collaborating centres in 20 countries. After a 6-week active run-in period, 11 140 patients with type 2 diabetes were randomised to treatment with a fixed combination of perindopril and indapamide or matching placebo, in addition to current therapy. The primary endpoints were composites of major macrovascular and microvascular events, defined as death from cardiovascular disease, non-fatal stroke or non-fatal myocardial infarction, and new or worsening renal or diabetic eye disease, and analysis was by intention-to-treat. The macrovascular and microvascular composites were analysed jointly and separately. This trial is registered with ClinicalTrials.gov, number NCT00145925. After a mean of 4·3 years of follow-up, 73% of those assigned active treatment and 74% of those assigned control remained on randomised treatment. Compared with patients assigned placebo, those assigned active therapy had a mean reduction in systolic blood pressure of 5·6 mm Hg and diastolic blood pressure of 2·2 mm Hg. The relative risk of a major macrovascular or microvascular event was reduced by 9% (861 [15·5%] active vs 938 [16·8%] placebo; hazard ratio 0·91, 95% CI 0·83–1·00, p=0·04). The separate reductions in macrovascular and microvascular events were similar but were not independently significant (macrovascular 0·92; 0·81–1·04, p=0·16; microvascular 0·91; 0·80–1·04, p=0·16). The relative risk of death from cardiovascular disease was reduced by 18% (211 [3·8%] active vs 257 [4·6%] placebo; 0·82, 0·68–0·98, p=0·03) and death from any cause was reduced by 14% (408 [7·3%] active vs 471 [8·5%] placebo; 0·86, 0·75–0·98, p=0·03). There was no evidence that the effects of the study treatment differed by initial blood pressure level or concomitant use of other treatments at baseline. Routine administration of a fixed combination of perindopril and indapamide to patients with type 2 diabetes was well tolerated and reduced the risks of major vascular events, including death. Although the confidence limits were wide, the results suggest that over 5 years, one death due to any cause would be averted among every 79 patients assigned active therapy.

Introduction Alcohol consumption is a risk factor for several types of cancer. Alcohol consumption levels in Argentina are among the highest in the world, and malignant neoplasms are the second cause of death in the country. Public health strategies aimed at reducing alcohol consumption could possibly lead to a decrease in cancer burden. Alcohol-attributable burden has been estimated before in neighboring countries Chile and Brazil. We now aimed to quantify the burden for Argentina. Methods We obtained data on alcohol consumption levels from a national representative health survey and etiologic effect sizes for the association between alcohol and cancer from the most recent comprehensive meta-analysis. We estimated the number of alcohol-attributable cancer-related deaths and disability-adjusted life years (DALYs), stratified by consumption level (light (0.1–12.5 g/day), moderate (12.6–50 g/day), or heavy (> 50 g/day) drinking). We additionally explored which hypothetical scenario would achieve the highest reduction in alcohol-attributable cancer burden: 1) heavy drinkers shifting to moderate drinking or 2) moderate drinkers shifting to light drinking. Results In 2018, 53% of the Argentinean population consumed alcohol. In men 3.7% of all cancer deaths and DALYs were attributable to alcohol consumption, in women this was 0.8% of all cancer deaths and DALYs. When moderate drinkers would shift to light drinking, 46% of alcohol-attributable cancer deaths and DALYs would be prevented, opposed to only 24% when heavy drinkers would shift to moderate drinking. Conclusion Most cancer deaths and DALYs were attributable to moderate alcohol consumption (50%). This calls for implementation of population-wide strategies—instead of targeting heavy drinking only—to effectively reduce harmful use of alcohol and its impact on disease burden.

Aims/hypothesis Available multivariable equations for cardiovascular risk assessment in people with diabetes have been derived either from the general population or from populations with diabetes. Their utility and comparative performance in a contemporary group of patients with type 2 diabetes are not well established. The aim of this study was to evaluate the performance of the Framingham and UK Prospective Diabetes Study (UKPDS) risk equations in participants who took part in the Action in Diabetes and Vascular disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) trial. Methods The 4-year risks of cardiovascular disease (CVD) and its constituents were estimated using two published Framingham and the UKPDS risk equations in 7,502 individuals with type 2 diabetes without prior known CVD at their enrolment in the trial. Results The risk of major CVD was overestimated by 170% (95% CI 146–195%) and 202% (176–231%) using the two Framingham equations. The risk of major coronary heart disease was overestimated by 198% (162–238%) with the UKPDS, and by 146% (117–179%) and 289% (243–341%) with the two different Framingham equations, respectively. The risks of stroke events were also overestimated with the UKPDS and one of the Framingham equations. The ability of these equations to rank risk among ADVANCE participants was modest, with c -statistics ranging from 0.57 to 0.71. Results stratified by sex, treatment allocation and ethnicity were broadly similar. Conclusions/interpretation Application of the Framingham and UKPDS risk equations to a contemporary treated group of patients with established type 2 diabetes is likely to substantially overestimate cardiovascular risk.