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      Effect of fenofibrate in 1113 patients at low-density lipoprotein cholesterol goal but high triglyceride levels: Real-world results and factors associated with triglyceride reduction

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          Abstract

          Fibrates are used in patients with dyslipidemia and high cardiovascular risk. However, information regarding drug response to fibrate has been highly limited. We investigated treatment results and factors associated with triglyceride reduction after fenofibrate therapy using large-scale real-world data. Patients with one or more cardiovascular risk factors, at low-density lipoprotein-cholesterol goal but with triglyceride level ≥150 mg/dL, and undergoing treatment with fenofibrate 135–160 mg for the first time were included in this retrospective observational study. The outcome variable was the percentage changes of TG levels. The achievement rate of triglyceride <150 mg/dL was additionally analyzed. Factors associated with treatment results were also analyzed. Among 2546 patients who were initially screened, 1113 patients were enrolled (median age: 61 years; male: 71%). After median follow-up of 4 months, the median change in triglyceride was -60%, and 49% of the patients reached triglyceride <150 mg/dL. After adjusting for confounding variables, female sex, non-diabetic status, coronary artery disease, lower baseline triglyceride, and no statin use were identified to be independently associated with achievement of triglyceride <150 mg/dL. Among them, female sex, non-diabetic status, and coronary artery disease were also related to median or greater percentage reduction of triglyceride. In conclusion, only half of the study patients reached triglyceride levels <150 mg/dL after real-world fenofibrate therapy. This study indicates that more attention is needed on some subgroups to obtain optimal triglyceride levels when treating with fenofibrate.

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          National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1 - executive summary.

          Various organizations and agencies have issued recommendations for the management of dyslipidemia. Although many commonalities exist among them, material differences are present as well. The leadership of the National Lipid Association (NLA) convened an Expert Panel to develop a consensus set of recommendations for patient-centered management of dyslipidemia in clinical medicine. The current Executive Summary highlights the major conclusions in Part 1 of the recommendations report of the NLA Expert Panel and includes: (1) background and conceptual framework for formulation of the NLA Expert Panel recommendations; (2) screening and classification of lipoprotein lipid levels in adults; (3) targets for intervention in dyslipidemia management; (4) atherosclerotic cardiovascular disease risk assessment and treatment goals based on risk category; (5) atherogenic cholesterol-non-high-density lipoprotein cholesterol and low-density lipoprotein cholesterol-as the primary targets of therapy; and (6) lifestyle and drug therapies intended to reduce morbidity and mortality associated with dyslipidemia.
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            Hypertriglyceridemia: its etiology, effects and treatment.

            Elevated plasma triglyceride concentration is a common biochemical finding, but the evidence for the benefit of treating this lipid disturbance remains less robust than that for treating elevated low-density lipoprotein-cholesterol. Part of the difficulty in the provision of specific recommendations has been the frequent coexistence of elevated triglycerides with other conditions that affect cardiovascular disease risk, such as depressed high-density lipoprotein-cholesterol, obesity, metabolic syndrome, proinflammatory and prothrombotic biomarkers, and type 2 diabetes. Recent investigations of outcomes of cardiovascular disease when medications are used to reduce triglyceride levels suggest that, although a net benefit probably exists, both relative and absolute risk reductions seem underwhelming when compared with the benefit of reducing low-density lipoprotein-cholesterol levels with treatment. However, the totality of evidence suggests that elevated triglyceride levels likely contribute independently to increased risk of cardiovascular disease, although there is no consensus about appropriate target levels. Furthermore, severe hypertriglyceridemia is associated with an increased risk of acute pancreatitis, irrespective of its effect on risk of cardiovascular disease. We review the causes and classification of elevated triglyceride levels, the clinical manifestations of primary hypertriglyceridemia and the management of patients with elevated triglyceride levels.
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              Predictors of nonadherence to statins: a systematic review and meta-analysis.

              Nonadherence to statins limits the benefits of this common drug class. Individual studies assessing predictors of nonadherence have produced inconsistent results. To identify reliable predictors of nonadherence to statins through systematic review and meta-analysis. Multiple databases, including MEDLINE, EMBASE, and PsycINFO, were searched (from inception through February 2009) to identify studies that evaluated predictors of nonadherence to statins. Studies were selected using a priori defined criteria, and each study was reviewed by 2 authors who abstracted data on study characteristics and outcomes. Relative risks were then pooled, using an inverse-variance weighted random-effects model. Twenty-two cohort studies met inclusion criteria. Age had a U-shaped association with adherence; the oldest (>/=70 years) and youngest (<50 years) subjects had lower adherence than the middle-aged (50-69 years) subjects. Women and patients with lower incomes were more likely to be nonadherent than were men (odds of nonadherence 1.07; 95% CI 1.04 to 1.11) and those with higher incomes (odds of nonadherence 1.18; 95% CI 1.10 to 1.28), respectively. A history of cardiovascular disease predicted better adherence to statins (odds of nonadherence 0.68; 95% CI 0.66 to 0.78). Similarly, a diagnosis of hypertension or diabetes was associated with better adherence. Although there were too few studies for quantitative pooling, increased testing of lipid levels and lower out-of-pocket costs appeared to be associated with better adherence. There was substantial (I(2) range 68.7-96.3%) heterogeneity between studies across factors. Several sociodemographic, medical, and health-care utilization characteristics are associated with statin nonadherence. These factors may be useful guides for targeting statin adherence interventions.
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                Author and article information

                Contributors
                Role: Formal analysisRole: Writing – original draft
                Role: Formal analysis
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                4 October 2018
                2018
                : 13
                : 10
                : e0205006
                Affiliations
                [1 ] Division of Cardiology, Department of Internal Medicine, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Korea
                [2 ] Department of Biostatistics and Computing, Yonsei University College of Medicine, Seoul, Korea
                [3 ] Division of Cardiology, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
                [4 ] Cardiovascular Research Institute, Yonsei University College of Medicine, Seoul, Korea
                University of Milano, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-4390-2915
                http://orcid.org/0000-0002-4535-3745
                Article
                PONE-D-18-14376
                10.1371/journal.pone.0205006
                6171908
                30286170
                59e1d5c6-d9c6-4c5b-901b-c8c8b6a5ec04
                © 2018 Woo et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 May 2018
                : 18 September 2018
                Page count
                Figures: 1, Tables: 3, Pages: 10
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: 2017R1D1B03029399
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: 2015M3A9B6029138
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003569, Ministry of Food and Drug Safety;
                Award ID: 18182MFD410
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008783, National Research Council of Science and Technology;
                Award ID: CAP-12-2-KBSI
                Award Recipient :
                This research was financially supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (2017R1D1B03029399), the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP (2015M3A9B6029138), the Ministry of Food and Drug Safety, Korea (18182MFD410), and the National Research Council of Science & Technology grant by the Korean government, MSIP (No. CAP-12-2-KBSI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Vascular Medicine
                Coronary Heart Disease
                Medicine and Health Sciences
                Cardiology
                Coronary Heart Disease
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Dyslipidemia
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Statins
                Biology and Life Sciences
                Biochemistry
                Lipids
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Regression Analysis
                Biology and Life Sciences
                Biochemistry
                Lipids
                Cholesterol
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Hypertension
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                All relevant data are within the paper and its Supporting Information files.

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