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Importance It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). Objective To estimate associations between major cardiovascular risk factors and VTE, i.e., deep-vein thrombosis (DVT) and pulmonary embolism (PE). Design Analysis of individual-participant data from the Emerging Risk Factors Collaboration (ERFC; 731,728 participants; 75 cohorts; latest date of follow-up 2015), and UK Biobank (UKBB; 421,537 participants; latest date of follow-up 2016). Setting Approximately population-based prospective cohort studies. Participants Individuals without cardiovascular disease at baseline. Exposures A panel of several established cardiovascular risk factors. Main Outcomes and Measures Hazard ratios (HRs) per 1-SD higher risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (n=1041 VTE, n=25,131 CHD) and incident fatal/non-fatal outcomes in UKBB (n=2321 VTE, n=3385 CHD). HRs were adjusted for age, sex, smoking status, diabetes mellitus, and body-mass index. Results Adjusted HRs for VTE were: 2.67 (2.45-2.91) in ERFC and 1.81 (1.71-1.92) in UKBB per decade older age; 1.38 (1.20-1.58) in ERFC and 1.23 (1.08-1.40) in UKBB with smoking; 1.43 (1.35-1.50) in ERFC and 1.37 (1.32-1.41) in UKBB per 1-SD higher body-mass index; and 0.75 (0.61-0.93) in ERFC and 0.82 (0.71-0.94) in UKBB with current alcohol consumption. For the preceding factors, there were similar HRs for pulmonary embolism versus deep vein thrombosis in UKBB (except adiposity was more strongly associated with PE; P, A study website (http://www.phpc.cam.ac.uk/ceu/erfc/list-of-studies/) includes a list that investigators have provided of funding agencies that have supported individual cohorts in the ERFC contributing to the present consortium. This research has been conducted using the UK Biobank resource (application 26865).

Publisher's version (útgefin grein), Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need., The work of the co-ordinating centre was funded by the UK Medical Research Council (G0800270), British Heart Foundation (SP/09/ 002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council (268834), and European Commission Framework Programme 7 (HEALTH-F2-2012-279233). The Emerging Risk Factor Collaboration’s website https://www.phpc.cam.ac.uk/ceu/erfc/list-of-studies/ has compiled a list provided by investigators of some of the funders of the component studies in this analysis. I.W. was supported by the Medical Research Council Unit Programme MC_UU_12023/21. M.K. is supported by the Netherlands Organization for Scientific Research (NWO) Veni grant (Veni, 91616079). J.P. is supported by Erasmus Mundus Western Balkans (ERAWEB), a project funded by the European Commission.

Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies.

We thank Kosmas Paraskevas for his interest in our study.The practice of medicine should be based on the best available evidence. The best evidence for when women lose their morphological suitability for endovascular aneurysm repair (EVAR) comes from the study of Sweet and colleagues, which showed that attenuation of the proportion of women suitable for EVAR comes only after the 5·5 cm threshold has been reached.It is well recognised that surgical mortality for most procedures increases with age, and increasing age might be one factor that influences the decision as whether to offer a woman EVAR. There are important competing risks to consider when offering any surgery with substantial operative mortality. Robust evidence for what age or aortic diameter a woman should be offered EVAR to maximise life-expectancy, quality of life, or cost-effectiveness does not exist. The new European Society of Vascular Surgery guidelines for the management of patients with abdominal aortic aneurysm (currently under review) are likely to recommend a threshold aortic diameter of 5·0 cm for intervention in women, but the uncertainty of the evidence is reflected by the level C, class 2b classification provisionally given to this evidence under the American Heart Association and European Society of Cardiology grading system. As such, Johansson and Harris are correct in pointing out that ideally “we need better evidence”

We thank Kosmas Paraskevas for his interest in our study.The practice of medicine should be based on the best available evidence. The best evidence for when women lose their morphological suitability for endovascular aneurysm repair (EVAR) comes from the study of Sweet and colleagues, which showed that attenuation of the proportion of women suitable for EVAR comes only after the 5·5 cm threshold has been reached.It is well recognised that surgical mortality for most procedures increases with age, and increasing age might be one factor that influences the decision as whether to offer a woman EVAR. There are important competing risks to consider when offering any surgery with substantial operative mortality. Robust evidence for what age or aortic diameter a woman should be offered EVAR to maximise life-expectancy, quality of life, or cost-effectiveness does not exist. The new European Society of Vascular Surgery guidelines for the management of patients with abdominal aortic aneurysm (currently under review) are likely to recommend a threshold aortic diameter of 5·0 cm for intervention in women, but the uncertainty of the evidence is reflected by the level C, class 2b classification provisionally given to this evidence under the American Heart Association and European Society of Cardiology grading system. As such, Johansson and Harris are correct in pointing out that ideally “we need better evidence”

Mendelian randomization is the use of genetic variants to make causal inferences from observational data. The field is currently undergoing a revolution fuelled by increasing numbers of genetic variants demonstrated to be associated with exposures in genome-wide association studies, and the public availability of summarized data on genetic associations with exposures and outcomes from large consortia. A Mendelian randomization analysis with many genetic variants can be performed relatively simply using summarized data. However, a causal interpretation is only assured if each genetic variant satisfies the assumptions of an instrumental variable. To provide some protection against failure of these assumptions, robust methods for instrumental variable analysis have been proposed. Here, we develop three extensions to instrumental variable methods using: i) robust regression, ii) the penalization of weights from candidate instruments with heterogeneous causal estimates, and iii) L1 penalization. Results from a wide variety of robust methods, including the recently-proposed MR-Egger and median-based methods, are compared in an extensive simulation study. We demonstrate that two methods, robust regression in an inverse-variance weighted method and a simple median of the causal estimates from the individual variants, have considerably improved Type 1 error rates compared with conventional methods in a wide variety of scenarios when up to 30% of the genetic variants are invalid instruments. While the MR-Egger method gives unbiased estimates when its assumptions are satisfied, these estimates are less efficient than those from other methods and are highly sensitive to violations of the assumptions. Methods that make different assumptions should be used routinely to assess the robustness of findings from applied Mendelian randomization investigations with multiple genetic variants.

IMPORTANCE The prevalence of cardiometabolic multimorbidity is increasing. OBJECTIVE To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. DESIGN, SETTING, AND PARTICIPANTS Age-and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689 300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128 843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499 808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). MAIN OUTCOMES AND MEASURES All-cause mortality and estimated reductions in life expectancy. RESULTS In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. CONCLUSIONS AND RELEVANCE Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

IMPORTANCE The value of measuring levels of glycated hemoglobin (HbA(1c)) for the prediction of first cardiovascular events is uncertain. OBJECTIVE To determine whether adding information on HbA(1c) values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (= 7.5%) risk. RESULTS During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA(1c) values and CVD risk. The association between HbA(1c) values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA(1c) was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA(1c) assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE In a study of individuals without known CVD or diabetes, additional assessment of HbA(1c) values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

Importance: Small abdominal aortic aneurysms (AAAs [3.0 cm-5.4 cm in diameter]) are monitored by ultrasound surveillance. The intervals between surveillance scans should be chosen to detect an expanding aneurysm prior to rupture. Objective: To limit risk of aneurysm rupture or excessive growth by optimizing ultrasound surveillance intervals. Data Sources and Study Selection: Individual patient data from studies of small AAA growth and rupture were assessed. Studies were identified for inclusion through a systematic literature search through December 2010. Study authors were contacted, which yielded 18 data sets providing repeated ultrasound measurements of AAA diameter over time in 15 471 patients. Data Extraction: AAA diameters were analyzed using a random-effects model that allowed for between-patient variability in size and growth rate. Rupture rates were analyzed by proportional hazards regression using the modeled AAA diameter as a time-varying covariate. Predictions of the risks of exceeding 5.5-cm diameter and of rupture within given time intervals were estimated and pooled across studies by random effects meta-analysis. Results: AAA growth and rupture rates varied considerably across studies. For each 0.5-cm increase in AAA diameter, growth rates increased on average by 0.59 mm per year (95% CI, 0.51-0.66) and rupture rates increased by a factor of 1.91 (95% CI, 1.61-2.25). For example, to control the AAA growth risk in men of exceeding 5.5 cm to below 10%, on average, a 7.4-year surveillance interval (95% CI, 6.7-8.1) is sufficient for a 3.0-cm AAA, while an 8-month interval (95% CI, 7-10) is necessary for a 5.0-cm AAA. To control the risk of rupture in men to below 1%, the corresponding estimated surveillance intervals are 8.5 years (95% CI, 7.0-10.5) and 17 months (95% CI, 14-22). Conclusion and Relevance: In contrast to the commonly adopted surveillance intervals in current AAA screening programs, surveillance intervals of several years may be clinically acceptable for the majority of patients with small AAA.

Background Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)), an inflammatory enzyme expressed in atherosclerotic plaques, is a therapeutic target being assessed in trials of vascular disease prevention. We investigated associations of circulating Lp-PLA(2) mass and activity with risk of coronary heart disease, stroke, and mortality under different circumstances. Methods With use of individual records from 79 036 participants in 32 prospective studies (yielding 17 722 incident fatal or non-fatal outcomes during 474 976 person-years at risk), we did a meta-analysis of within-study regressions to calculate risk ratios (RRs) per 1 SD higher value of Lp-PLA(2) or other risk factor. The primary outcome was coronary heart disease. Findings Lp-PLA(2) activity and mass were associated with each other (r=0.51, 95% CI 0.47-0.56) and proatherogenic lipids. We noted roughly log-linear associations of Lp-PLA(2) activity and mass with risk of coronary heart disease and vascular death. RRs, adjusted for conventional risk factors, were: 1.10 (95% CI 1.05-1.16) with Lp-PLA(2) activity and 1.11 (1.07-1.16) with Lp-PLA(2) mass for coronary heart disease; 1.08 (0.97-1.20) and 1.14 (1.02-1.27) for ischaemic stroke; 1.16 (1.09-1.24) and 1.13 (1.05-1.22) for vascular mortality; and 1.10 (1.04-1.17) and 1.10 (1.03-1.18) for non-vascular mortality, respectively. RRs with Lp-PLA(2) did not differ significantly in people with and without initial stable vascular disease, apart from for vascular death with Lp-PLA(2) mass. Adjusted RRs for coronary heart disease were 1.10 (1.02-1.18) with non-HDL cholesterol and 1.10 (1.00-1.21) with systolic blood pressure. Interpretation Lp-PLA(2) activity and mass each show continuous associations with risk of coronary heart disease, similar in magnitude to that with non-HDL cholesterol or systolic blood pressure in this population. Associations of Lp-PLA(2) mass and activity are not exclusive to vascular outcomes, and the vascular associations depend at least partly on lipids. Funding UK Medical Research Council, GlaxoSmithKline, and British Heart Foundation.

OBJECTIVE: Carotid intima-media thickness (CIMT) is a marker of subclinical organ damage and predicts cardiovascular disease (CVD) events in the general population. It has also been associated with vascular risk in people with diabetes. However, the association of CIMT change in repeated examinations with subsequent CVD events is uncertain, and its use as a surrogate end point in clinical trials is controversial. We aimed at determining the relation of CIMT change to CVD events in people with diabetes. RESEARCH DESIGN AND METHODS: In a comprehensive meta-analysis of individual participant data, we collated data from 3,902 adults (age 33-92 years) with type 2 diabetes from 21 population-based cohorts. We calculated the hazard ratio (HR) per standard deviation (SD) difference in mean common carotid artery intima-media thickness (CCA-IMT) or in CCA-IMT progression, both calculated from two examinations on average 3.6 years apart, for each cohort, and combined the estimates with random-effects meta-analysis. RESULTS: Average mean CCA-IMT ranged from 0.72 to 0.97 mm across cohorts in people with diabetes. The HR of CVD events was 1.22 (95% CI 1.12-1.33) per SD difference in mean CCA-IMT, after adjustment for age, sex, and cardiometabolic risk factors. Average mean CCA-IMT progression in people with diabetes ranged between -0.09 and 0.04 mm/year. The HR per SD difference in mean CCA-IMT progression was 0.99 (0.91-1.08). CONCLUSIONS: Despite reproducing the association between CIMT level and vascular risk in subjects with diabetes, we did not find an association between CIMT change and vascular risk. These results do not support the use of CIMT progression as a surrogate end point in clinical trials in people with diabetes.

AIMS: Carotid intima media thickness (CIMT) predicts cardiovascular (CVD) events, but the predictive value of CIMT change is debated. We assessed the relation between CIMT change and events in individuals at high cardiovascular risk. METHODS AND RESULTS: From 31 cohorts with two CIMT scans (total n = 89070) on average 3.6 years apart and clinical follow-up, subcohorts were drawn: (A) individuals with at least 3 cardiovascular risk factors without previous CVD events, (B) individuals with carotid plaques without previous CVD events, and (C) individuals with previous CVD events. Cox regression models were fit to estimate the hazard ratio (HR) of the combined endpoint (myocardial infarction, stroke or vascular death) per standard deviation (SD) of CIMT change, adjusted for CVD risk factors. These HRs were pooled across studies. In groups A, B and C we observed 3483, 2845 and 1165 endpoint events, respectively. Average common CIMT was 0.79mm (SD 0.16mm), and annual common CIMT change was 0.01mm (SD 0.07mm), both in group A. The pooled HR per SD of annual common CIMT change (0.02 to 0.43mm) was 0.99 (95% confidence interval: 0.95-1.02) in group A, 0.98 (0.93-1.04) in group B, and 0.95 (0.89-1.04) in group C. The HR per SD of common CIMT (average of the first and the second CIMT scan, 0.09 to 0.75mm) was 1.15 (1.07-1.23) in group A, 1.13 (1.05-1.22) in group B, and 1.12 (1.05-1.20) in group C. CONCLUSIONS: We confirm that common CIMT is associated with future CVD events in individuals at high risk. CIMT change does not relate to future event risk in high-risk individuals.

IMPORTANCE: It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). OBJECTIVE: To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. DESIGN, SETTING, AND PARTICIPANTS: This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731 728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421 537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. EXPOSURES: A panel of several established cardiovascular risk factors. MAIN OUTCOMES AND MEASURES: Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25 131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). RESULTS: Of the 731 728 participants from the ERFC, 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421 537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. CONCLUSIONS AND RELEVANCE: Older age, smoking, and adiposity were consistently associated with higher VTE risk.

BACKGROUND: A third of deaths in the UK from ruptured abdominal aortic aneurysm (AAA) are in women. In men, national screening programmes reduce deaths from AAA and are cost-effective. The benefits, harms, and cost-effectiveness in offering a similar programme to women have not been formally assessed, and this was the aim of this study. METHODS: We developed a decision model to assess predefined outcomes of death caused by AAA, life years, quality-adjusted life years, costs, and the incremental cost-effectiveness ratio for a population of women invited to AAA screening versus a population who were not invited to screening. A discrete event simulation model was set up for AAA screening, surveillance, and intervention. Relevant women-specific parameters were obtained from sources including systematic literature reviews, national registry or administrative databases, major AAA surgery trials, and UK National Health Service reference costs. FINDINGS: AAA screening for women, as currently offered to UK men (at age 65 years, with an AAA diagnosis at an aortic diameter of ≥3·0 cm, and elective repair considered at ≥5·5cm) gave, over 30 years, an estimated incremental cost-effectiveness ratio of £30 000 (95% CI 12 000-87 000) per quality-adjusted life year gained, with 3900 invitations to screening required to prevent one AAA-related death and an overdiagnosis rate of 33%. A modified option for women (screening at age 70 years, diagnosis at 2·5 cm and repair at 5·0 cm) was estimated to have an incremental cost-effectiveness ratio of £23 000 (9500-71 000) per quality-adjusted life year and 1800 invitations to screening required to prevent one AAA-death, but an overdiagnosis rate of 55%. There was considerable uncertainty in the cost-effectiveness ratio, largely driven by uncertainty about AAA prevalence, the distribution of aortic sizes for women at different ages, and the effect of screening on quality of life. INTERPRETATION: By UK standards, an AAA screening programme for women, designed to be similar to that used to screen men, is unlikely to be cost-effective. Further research on the aortic diameter distribution in women and potential quality of life decrements associated with screening are needed to assess the full benefits and harms of modified options. FUNDING: UK National Institute for Health Research Health Technology Assessment programme.

Importance The prevalence of cardiometabolic multimorbidity is increasing. Objective To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. Design, Setting, and Participants Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689 300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128 843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499 808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. Exposures A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). Main Outcomes and Measures All-cause mortality and estimated reductions in life expectancy. Results In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. Conclusions and Relevance Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

Supplemental material, DS_10.1177_0272989X17753380 for Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening by Matthew J. Glover, Edmund Jones, Katya L. Masconi, Michael J. Sweeting, Simon G. Thompson, and SWAN Collaborators in Medical Decision Making

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

Supplemental material, DS_10.1177_0272989X17753380 for Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening by Matthew J. Glover, Edmund Jones, Katya L. Masconi, Michael J. Sweeting, Simon G. Thompson, and SWAN Collaborators in Medical Decision Making

BACKGROUND: The INTERVAL trial showed that, over a 2-year period, inter-donation intervals for whole blood donation can be safely reduced to meet blood shortages. We extended the INTERVAL trial for a further 2 years to evaluate the longer-term risks and benefits of varying inter-donation intervals, and to compare routine versus more intensive reminders to help donors keep appointments. METHODS: The INTERVAL trial was a parallel group, pragmatic, randomised trial that recruited blood donors aged 18 years or older from 25 static donor centres of NHS Blood and Transplant across England, UK. Here we report on the prespecified analyses after 4 years of follow-up. Participants were whole blood donors who agreed to continue trial participation on their originally allocated inter-donation intervals (men: 12, 10, and 8 weeks; women: 16, 14, and 12 weeks). They were further block-randomised (1:1) to routine versus more intensive reminders using computer-generated random sequences. The prespecified primary outcome was units of blood collected per year analysed in the intention-to-treat population. Secondary outcomes related to safety were quality of life, self-reported symptoms potentially related to donation, haemoglobin and ferritin concentrations, and deferrals because of low haemoglobin and other factors. This trial is registered with ISRCTN, number ISRCTN24760606, and has completed. FINDINGS: Between Oct 19, 2014, and May 3, 2016, 20 757 of the 38 035 invited blood donors (10 843 [58%] men, 9914 [51%] women) participated in the extension study. 10 378 (50%) were randomly assigned to routine reminders and 10 379 (50%) were randomly assigned to more intensive reminders. Median follow-up was 1·1 years (IQR 0·7-1·3). Compared with routine reminders, more intensive reminders increased blood collection by a mean of 0·11 units per year (95% CI 0·04-0·17; p=0·0003) in men and 0·06 units per year (0·01-0·11; p=0·0094) in women. During the extension study, each week shorter inter-donation interval increased blood collection by a mean of 0·23 units per year (0·21-0·25) in men and 0·14 units per year (0·12-0·15) in women (both p0.0001 for tests of linear trend by inter-donation intervals) other than a higher reported frequency of doctor-diagnosed low iron concentrations and prescription of iron supplements in men (p

BACKGROUND: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease. METHODS: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th-95th percentile 1·04-13·5]) from 71 011 participants from 37 studies. FINDINGS: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1·14, 95% CI, 1·10-1·17), coronary disease excluding myocardial infarction (1·06, 1·00-1·11), heart failure (1·09, 1·03-1·15), fatal hypertensive disease (1·24, 1·15-1·33); and fatal aortic aneurysm (1·15, 1·03-1·28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0·94, 0·91-0·97). In comparison to those who reported drinking >0-≤100 g per week, those who reported drinking >100-≤200 g per week, >200-≤350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively. INTERPRETATION: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines.

Very-early-onset inflammatory bowel disease (VEO-IBD) is a heterogeneous phenotype associated with a spectrum of rare Mendelian disorders. Here, we perform whole-exome-sequencing and genome-wide genotyping in 145 patients (median age-at-diagnosis of 3.5 years), in whom no Mendelian disorders were clinically suspected. In five patients we detect a primary immunodeficiency or enteropathy, with clinical consequences (XIAP, CYBA, SH2D1A, PCSK1). We also present a case study of a VEO-IBD patient with a mosaic de novo, pathogenic allele in CYBB. The mutation is present in ~70% of phagocytes and sufficient to result in defective bacterial handling but not life-threatening infections. Finally, we show that VEO-IBD patients have, on average, higher IBD polygenic risk scores than population controls (99 patients and 18,780 controls; P < 4 × 10−10), and replicate this finding in an independent cohort of VEO-IBD cases and controls (117 patients and 2,603 controls; P < 5 × 10−10). This discovery indicates that a polygenic component operates in VEO-IBD pathogenesis.

OBJECTIVE: To use genetic variants as unconfounded proxies of C reactive protein concentration to study its causal role in coronary heart disease. DESIGN: Mendelian randomisation meta-analysis of individual participant data from 47 epidemiological studies in 15 countries. PARTICIPANTS: 194 418 participants, including 46 557 patients with prevalent or incident coronary heart disease. Information was available on four CRP gene tagging single nucleotide polymorphisms (rs3093077, rs1205, rs1130864, rs1800947), concentration of C reactive protein, and levels of other risk factors. MAIN OUTCOME MEASURES: Risk ratios for coronary heart disease associated with genetically raised C reactive protein versus risk ratios with equivalent differences in C reactive protein concentration itself, adjusted for conventional risk factors and variability in risk factor levels within individuals. RESULTS: CRP variants were each associated with up to 30% per allele difference in concentration of C reactive protein (P