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      High Serum Immunoglobulin G and M Levels Predict Freedom From Adverse Cardiovascular Events in Hypertension: A Nested Case-Control Substudy of the Anglo-Scandinavian Cardiac Outcomes Trial

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          Abstract

          Aims

          We aimed to determine whether the levels of total serum IgM and IgG, together with specific antibodies against malondialdehyde-conjugated low-density lipoprotein (MDA-LDL), can improve cardiovascular risk discrimination.

          Methods and Results

          The Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT) randomized 9098 patients in the UK and Ireland into the Blood Pressure-Lowering Arm. 485 patients that had cardiovascular (CV) events over 5.5 years were age and sex matched with 1367 controls. Higher baseline total serum IgG, and to a lesser extent IgM, were associated with decreased risk of CV events (IgG odds ratio (OR) per one standard deviation (SD) 0.80 [95% confidence interval, CI 0.72,0.89], p < 0.0001; IgM 0.83[0.75,0.93], p = 0.001), and particularly events due to coronary heart disease (CHD) (IgG OR 0.66 (0.57,0.76); p < 0.0001, IgM OR 0.81 (0.71,0.93); p = 0.002). The association persisted after adjustment for a basic model with variables in the Framingham Risk Score (FRS) as well as following inclusion of C-reactive protein (CRP) and N-terminal pro-B-type natriuretic peptide (NtProBNP). IgG and IgM antibodies against MDA-LDL were also associated with CV events but their significance was lost following adjustment for total serum IgG and IgM respectively. The area under the receiver operator curve for CV events was improved from the basic risk model when adding in total serum IgG, and there was improvement in continuous and categorical net reclassification (17.6% and 7.5% respectively) as well as in the integrated discrimination index.

          Conclusion

          High total serum IgG levels are an independent predictor of freedom from adverse cardiovascular events, particularly those attributed to CHD, in patients with hypertension.

          Highlights

          • We studied whether immunoglobulins predict cardiovascular events in hypertension.

          • Total serum IgG was strongly associated with freedom from adverse events.

          • The predictive power of total IgG was superior to antibodies against MDA-LDL.

          • Total serum IgG significantly improved cardiovascular risk reclassification.

          • Further work is needed to determine whether these observations extend to other populations.

          Current clinical tools for stratifying cardiovascular risk remain relatively imprecise. In view of interests in the immune system in atherosclerosis, our study explored whether measuring IgG and IgM immunoglobulin levels provides any improvement in determining risk in hypertensive patients. We found that high levels of total serum IgG, and to a lesser extent IgM, were strongly associated with freedom from coronary events. We also found that antibodies against one type of oxidized LDL conferred protection, but the effect was weaker than with total immunoglobulins. Our results support a link between robust humoral immunity and cardiac health.

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          Most cited references43

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          Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

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            Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

            Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance as new tests are developed and marketed. When a test is based on an observed variable that lies on a continuous or graded scale, an assessment of the overall value of the test can be made through the use of a receiver operating characteristic (ROC) curve. The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates. When two or more empirical curves are constructed based on tests performed on the same individuals, statistical analysis on differences between curves must take into account the correlated nature of the data. This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
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              Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers.

              Appropriate quantification of added usefulness offered by new markers included in risk prediction algorithms is a problem of active research and debate. Standard methods, including statistical significance and c statistic are useful but not sufficient. Net reclassification improvement (NRI) offers a simple intuitive way of quantifying improvement offered by new markers and has been gaining popularity among researchers. However, several aspects of the NRI have not been studied in sufficient detail. In this paper we propose a prospective formulation for the NRI which offers immediate application to survival and competing risk data as well as allows for easy weighting with observed or perceived costs. We address the issue of the number and choice of categories and their impact on NRI. We contrast category-based NRI with one which is category-free and conclude that NRIs cannot be compared across studies unless they are defined in the same manner. We discuss the impact of differing event rates when models are applied to different samples or definitions of events and durations of follow-up vary between studies. We also show how NRI can be applied to case-control data. The concepts presented in the paper are illustrated in a Framingham Heart Study example. In conclusion, NRI can be readily calculated for survival, competing risk, and case-control data, is more objective and comparable across studies using the category-free version, and can include relative costs for classifications. We recommend that researchers clearly define and justify the choices they make when choosing NRI for their application. Copyright © 2010 John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
                Journal
                EBioMedicine
                EBioMedicine
                EBioMedicine
                Elsevier
                2352-3964
                20 June 2016
                July 2016
                20 June 2016
                : 9
                : 372-380
                Affiliations
                [a ]Vascular Sciences Section, NHLI, Imperial College London, United Kingdom
                [b ]International Centre for Circulatory Health, NHLI, Imperial College London, United Kingdom
                [c ]Institute of Cardiovascular Science, University College London, United Kingdom
                [d ]Division of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom
                Author notes
                [* ]Corresponding author at: Vascular Sciences Section, Imperial College Centre for Translational and Experimental Medicine, Hammersmith Campus, Du Cane Road, London W12 0NN, United Kingdom.Vascular Sciences SectionImperial College Centre for Translational and Experimental MedicineHammersmith CampusDu Cane RoadLondonW12 0NNUnited Kingdom d.haskard@ 123456imperial.ac.uk
                [1]

                Joint senior author.

                Article
                S2352-3964(16)30256-0
                10.1016/j.ebiom.2016.06.012
                4972545
                27333022
                6640fbf0-6039-4712-bfe4-5848bc78aacc
                © 2016 The Authors. Published by Elsevier B.V.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 25 April 2016
                : 20 May 2016
                : 6 June 2016
                Categories
                Research Paper

                immunoglobulins,anti-oxidized-ldl antibodies,cardiovascular risk stratification

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