Association of small, dense LDL-cholesterol concentration and lipoprotein particle characteristics with coronary heart disease: A systematic review and meta-analysis

Objectives: The aim of this study was to systematically collate and appraise the available evidence regarding the associations between small, dense low-density lipoprotein (sdLDL) and incident coronary heart disease (CHD), focusing on cholesterol concentration (sdLDL-C) and sdLDL particle characteristics (presence, density, and size). Background: Coronary heart disease (CHD) is the leading cause of death worldwide. Small, dense low-density lipoprotein (sdLDL) has been hypothesized to induce atherosclerosis and subsequent coronary heart disease (CHD). However, the etiological relevance of lipoprotein particle size (sdLDL) versus cholesterol content (sdLDL-C) remains unclear. Methods: PubMed, MEDLINE, Web of Science, and EMBASE were systematically searched for studies published before February 2020. CHD associations were based on quartile comparisons in eight studies of sdLDL-C and were based on binary categorization in fourteen studies of sdLDL particle size. Reported hazards ratios (HR) and odds ratios (OR) with 95% confidence interval (CI) were standardized and pooled using a random-effects meta-analysis model. Results: Data were collated from 21 studies with a total of 30,628 subjects and 5,693 incident CHD events. The average age was 67 years, and 53% were men. Higher sdLDL and sdLDL-C levels were both significantly associated with higher risk of CHD. The pooled estimate for the high vs. low categorization of sdLDL was 1.36 (95% CI: 1.21, 1.52) and 1.07 (95% CI: 1.01, 1.12) for comparing the top quartiles versus the bottom of sdLDL-C. Several studies suggested a dose response relationship. Conclusions: The findings show a positive association between sdLDL or sdLDL-C levels and CHD, which is supported by an increasing body of genetic evidence in favor of its causality as an etiological risk factor. Thus, the results support sdLDL and sdLDL-C as a risk marker, but further research is required to establish sdLDL or sdLDL-C as a potential therapeutic marker for incident CHD risk reduction

Modeling the costs and long-term health benefits of screening the general population for risks of cardiovascular disease: a review of methods used in the literature.

BACKGROUND: Strategies for screening and intervening to reduce the risk of cardiovascular disease (CVD) in primary care settings need to be assessed in terms of both their costs and long-term health effects. We undertook a literature review to investigate the methodologies used. METHODS: In a framework of developing a new health-economic model for evaluating different screening strategies for primary prevention of CVD in Europe (EPIC-CVD project), we identified seven key modeling issues and reviewed papers published between 2000 and 2013 to assess how they were addressed. RESULTS: We found 13 relevant health-economic modeling studies of screening to prevent CVD in primary care. The models varied in their degree of complexity, with between two and 33 health states. Programmes that screen the whole population by a fixed cut-off (e.g., predicted 10-year CVD risk >20 %) identify predominantly elderly people, who may not be those most likely to benefit from long-term treatment. Uncertainty and model validation were generally poorly addressed. Few studies considered the disutility of taking drugs in otherwise healthy individuals or the budget impact of the programme. CONCLUSIONS: Model validation, incorporation of parameter uncertainty, and sensitivity analyses for assumptions made are all important components of model building and reporting, and deserve more attention. Complex models may not necessarily give more accurate predictions. Availability of a large enough source dataset to reliably estimate all relevant input parameters is crucial for achieving credible results. Decision criteria should consider budget impact and the medicalization of the population as well as cost-effectiveness thresholds.This work was financially supported by the EPIC-CVD project. EPIC-CVD is a European Commision funded project under the Health theme of Seventh Framework Programme that builds on EPIC-Heart, which has been funded by the Medical Research Council, the British Heart Foundation and European Research Council Advanced Investigator Award.This is the author accepted manuscript. It is currently embargoed pending publication

Travel Is a Key Risk Factor for Malaria Transmission in Pre-Elimination Settings in Sub-Saharan Africa: A Review of the Literature and Meta-Analysis.

By sustaining transmission or causing malaria outbreaks, imported malaria undermines malaria elimination efforts. Few studies have examined the impact of travel on malaria epidemiology. We conducted a literature review and meta-analysis of studies investigating travel as a risk factor for malaria infection in sub-Saharan Africa using PubMed. We identified 22 studies and calculated a random-effects meta-analysis pooled odds ratio (OR) of 3.77 (95% CI: 2.49-5.70), indicating that travel is a significant risk factor for malaria infection. Odds ratios were particularly high in urban locations when travel was to rural areas, to more endemic/high transmission areas, and in young children. Although there was substantial heterogeneity in the magnitude of association across the studies, the pooled estimate and directional consistency support travel as an important risk factor for malaria infection

Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Background Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure–risk relationships, but involves a number of analytical challenges. Methods This article describes statistical approaches adopted in the Emerging Risk Factors Collaboration, in which primary data from more than 1 million participants in more than 100 prospective studies have been collated to enable detailed analyses of various risk markers in relation to incident cardiovascular disease outcomes. Results Analyses have been principally based on Cox proportional hazards regression models stratified by sex, undertaken in each study separately. Estimates of exposure–risk relationships, initially unadjusted and then adjusted for several confounders, have been combined over studies using meta-analysis. Methods for assessing the shape of exposure–risk associations and the proportional hazards assumption have been developed. Estimates of interactions have also been combined using meta-analysis, keeping separate within- and between-study information. Regression dilution bias caused by measurement error and within-person variation in exposures and confounders has been addressed through the analysis of repeat measurements to estimate corrected regression coefficients. These methods are exemplified by analysis of plasma fibrinogen and risk of coronary heart disease, and Stata code is made available. Conclusion Increasing numbers of meta-analyses of individual participant data from observational data are being conducted to enhance the statistical power and detail of epidemiological studies. The statistical methods developed here can be used to address the needs of such analyses

Longitudinal association of C-reactive protein and Haemoglobin A1c over 13 years: the European Prospective Investigation into Cancer - Norfolk study

Abstract Background Type-2 diabetes is associated with systemic inflammation and higher C-reactive protein (CRP) levels. However, the longitudinal association of CRP and haemoglobin-A1c (HbA1c) has not been described in large prospective studies. Understanding such associations may shed light on the role of inflammation in development of type-2 diabetes and its complications such as cardiovascular diseases. Methods EPIC-Norfolk is a cohort study of men and women aged 40–79 years at time of recruitment (1993–1997). Serum CRP (mg/l) was measured using a high-sensitivity assay at baseline and 13-years follow-up. HbA1c (%) was measured at baseline, 4, and 13 years. Participants were excluded if they were diagnosed with diabetes or were taking diabetes medication. Data on at least one measurement of CRP and HbA1c was available for 14228 participants (55 % of the cohort). Results In the cross-sectional analysis of baseline data, a 1-SD higher loge-CRP (about three-fold higher CRP) was associated with 0.06 (95 % CI 0.04, 0.08) higher HbA1c (%) adjusted for potential confounders. In longitudinal analysis using multivariable linear mixed models, change in CRP over 13 years was to a similar extent positively associated with increase in HbA1c, such that 1-SD higher longitudinal change in loge-CRP was associated with 0.04 (95 % CI 0.02, 0.05) increase in HbA1c. Conclusion In this study we found longitudinal observational evidence suggesting that increase in systemic inflammation is associated with an increase in HbA1c and thus systemic inflammation may have a role in development of type-2 diabetes and its complications

Leucocyte telomere length and risk of cardiovascular disease: systematic review and meta-analysis.

OBJECTIVE: To assess the association between leucocyte telomere length and risk of cardiovascular disease. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Studies published up to March 2014 identified through searches of Medline, Web of Science, and Embase. ELIGIBILITY CRITERIA: Prospective and retrospective studies that reported on associations between leucocyte telomere length and coronary heart disease (defined as non-fatal myocardial infarction, coronary heart disease death, or coronary revascularisation) or cerebrovascular disease (defined as non-fatal stroke or death from cerebrovascular disease) and were broadly representative of general populations--that is, they did not select cohort or control participants on the basis of pre-existing cardiovascular disease or diabetes. RESULTS: Twenty four studies involving 43,725 participants and 8400 patients with cardiovascular disease (5566 with coronary heart disease and 2834 with cerebrovascular disease) were found to be eligible. In a comparison of the shortest versus longest third of leucocyte telomere length, the pooled relative risk for coronary heart disease was 1.54 (95% confidence interval 1.30 to 1.83) in all studies, 1.40 (1.15 to 1.70) in prospective studies, and 1.80 (1.32 to 2.44) in retrospective studies. Heterogeneity between studies was moderate (I(2) = 64%, 41% to 77%, Phet<0.001) and was not significantly explained by mean age of participants (P = 0.23), the proportion of male participants (P = 0.45), or distinction between retrospective versus prospective studies (P = 0.32). Findings for coronary heart disease were similar in meta-analyses restricted to studies that adjusted for conventional vascular risk factors (relative risk 1.42, 95% confidence interval 1.17 to 1.73); studies with ≥ 200 cases (1.44, 1.20 to 1.74); studies with a high quality score (1.53, 1.22 to 1.92); and in analyses that corrected for publication bias (1.34, 1.12 to 1.60). The pooled relative risk for cerebrovascular disease was 1.42 (1.11 to 1.81), with no significant heterogeneity between studies (I(2) = 41%, 0% to 72%, Phet = 0.08). Shorter telomeres were not significantly associated with cerebrovascular disease risk in prospective studies (1.14, 0.85 to 1.54) or in studies with a high quality score (1.21, 0.83 to 1.76). CONCLUSION: Available observational data show an inverse association between leucocyte telomere length and risk of coronary heart disease independent of conventional vascular risk factors. The association with cerebrovascular disease is less certain

Assessing risk prediction models using individual participant data from multiple studies.

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

Genomic risk prediction of coronary artery disease in women with breast cancer: a prospective cohort study.

Funder: Wellcome TrustBackgroundAdvancements in cancer therapeutics have resulted in increases in cancer-related survival; however, there is a growing clinical dilemma. The current balancing of survival benefits and future cardiotoxic harms of oncotherapies has resulted in an increased burden of cardiovascular disease in breast cancer survivors. Risk stratification may help address this clinical dilemma. This study is the first to assess the association between a coronary artery disease-specific polygenic risk score and incident coronary artery events in female breast cancer survivors.MethodsWe utilized the Studies in Epidemiology and Research in Cancer Heredity prospective cohort involving 12,413 women with breast cancer with genotype information and without a baseline history of cardiovascular disease. Cause-specific hazard ratios for association of the polygenic risk score and incident coronary artery disease (CAD) were obtained using left-truncated Cox regression adjusting for age, genotype array, conventional risk factors such as smoking and body mass index, as well as other sociodemographic, lifestyle, and medical variables.ResultsOver a median follow-up of 10.3 years (IQR: 16.8) years, 750 incident fatal or non-fatal coronary artery events were recorded. A 1 standard deviation higher polygenic risk score was associated with an adjusted hazard ratio of 1.33 (95% CI 1.20, 1.47) for incident CAD.ConclusionsThis study provides evidence that a coronary artery disease-specific polygenic risk score can risk-stratify breast cancer survivors independently of other established cardiovascular risk factors

Socioeconomic Deprivation and Survival After Heart Transplantation in England: An Analysis of the United Kingdom Transplant Registry.

BACKGROUND: Socioeconomic deprivation (SED) is associated with shorter survival across a range of cardiovascular and noncardiovascular diseases. The association of SED with survival after heart transplantation in England, where there is universal healthcare provision, is unknown. METHODS AND RESULTS: Long-term follow-up data were obtained for all patients in England who underwent heart transplantation between 1995 and 2014. We used the United Kingdom Index of Multiple Deprivation (UK IMD), a neighborhood level measure of SED, to estimate the relative degree of deprivation for each recipient. Cox proportional hazard models were used to examine the association between SED and overall survival and conditional survival (dependant on survival at 1 year after transplantation) during follow-up. Models were stratified by transplant center and adjusted for donor and recipient age and sex, ethnicity, serum creatinine, diabetes mellitus, and heart failure cause. A total of 2384 patients underwent heart transplantation. There were 1101 deaths during 17 040 patient-year follow-up. Median overall survival was 12.6 years, and conditional survival was 15.6 years. Comparing the most deprived with the least deprived quintile, adjusted hazard ratios for all-cause mortality were 1.27 (1.04-1.55; P=0.021) and 1.59 (1.22-2.09; P=0.001) in the overall and conditional models, respectively. Median overall survival and conditional survival were 3.4 years shorter in the most deprived quintile than in the least deprived. CONCLUSIONS: Higher SED is associated with shorter survival in heart transplant recipients in England and should be considered when comparing outcomes between centers. Future research should seek to identify modifiable mediators of this association.No direct funding was provided for the conduct of this study. JE completed part of this work as part of an academic clinical fellowship, where he spent time at the University of Cambridge, Cardiovascular Epidemiology Unit receiving training on research methods, supported by SK and EDA. The Cardiovascular Epidemiology Unit is funded by the UK Medical Research Council (G0800270), British Heart Foundation (SP/09/002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, and UK National Institute for Health Research Cambridge Biomedical Research Centre.This is the author accepted manuscript. The final version is available from American Heart Association via https://doi.org/10.1161/CIRCOUTCOMES.116.00265

The INTERVAL trial to determine whether intervals between blood donations can be safely and acceptably decreased to optimise blood supply: study protocol for a randomised controlled trial.

BACKGROUND: Ageing populations may demand more blood transfusions, but the blood supply could be limited by difficulties in attracting and retaining a decreasing pool of younger donors. One approach to increase blood supply is to collect blood more frequently from existing donors. If more donations could be safely collected in this manner at marginal cost, then it would be of considerable benefit to blood services. National Health Service (NHS) Blood and Transplant in England currently allows men to donate up to every 12 weeks and women to donate up to every 16 weeks. In contrast, some other European countries allow donations as frequently as every 8 weeks for men and every 10 weeks for women. The primary aim of the INTERVAL trial is to determine whether donation intervals can be safely and acceptably decreased to optimise blood supply whilst maintaining the health of donors. METHODS/DESIGN: INTERVAL is a randomised trial of whole blood donors enrolled from all 25 static centres of NHS Blood and Transplant. Recruitment of about 50,000 male and female donors started in June 2012 and was completed in June 2014. Men have been randomly assigned to standard 12-week versus 10-week versus 8-week inter-donation intervals, while women have been assigned to standard 16-week versus 14-week versus 12-week inter-donation intervals. Sex-specific comparisons will be made by intention-to-treat analysis of outcomes assessed after two years of intervention. The primary outcome is the number of blood donations made. A key secondary outcome is donor quality of life, assessed using the Short Form Health Survey. Additional secondary endpoints include the number of 'deferrals' due to low haemoglobin (and other factors), iron status, cognitive function, physical activity, and donor attitudes. A comprehensive health economic analysis will be undertaken. DISCUSSION: The INTERVAL trial should yield novel information about the effect of inter-donation intervals on blood supply, acceptability, and donors' physical and mental well-being. The study will generate scientific evidence to help formulate blood collection policies in England and elsewhere. TRIAL REGISTRATION: Current Controlled Trials ISRCTN24760606, 25 January 2012.The trial is funded by NHS Blood and Transplant. The trial’s coordinating centre at the Department of Public Health and Primary Care at the University of Cambridge has received core support from the UK Medical Research Council, British Heart Foundation, and the UK National Institute of Health Research (Cambridge Biomedical Research Centre). Investigators at the University of Oxford have been supported by Research and Development Programme of NHSBT, the NHSBT Howard Ostin Trust Fund, the UK National Institute of Health Research (Oxford Biomedical Research Centre) through the Programme Grant NIHR-RP-PG-0310-1004 and the Oxford Biomedical Research Centre.This is the published version of the article. It is published by BioMed Central in Trials here: http://www.trialsjournal.com/content/15/1/363