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      Sub-optimal cholesterol response to initiation of statins and future risk of cardiovascular disease

      , , , ,
      Heart
      BMJ

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          Abstract

          Objective

          To assess low-density lipoprotein cholesterol (LDL-C) response in patients after initiation of statins, and future risk of cardiovascular disease (CVD).

          Methods

          Prospective cohort study of 165 411 primary care patients, from the UK Clinical Practice Research Datalink, who were free of CVD before statin initiation, and had at least one pre-treatment LDL-C within 12 months before, and one post-treatment LDL-C within 24 months after, statin initiation. Based on current national guidelines, <40% reduction in baseline LDL-C within 24 months was classified as a sub-optimal statin response. Cox proportional regression and competing-risks survival regression models were used to determine adjusted hazard ratios (HRs) and sub-HRs for incident CVD outcomes for LDL-C response to statins.

          Results

          84 609 (51.2%) patients had a sub-optimal LDL-C response to initiated statin therapy within 24 months. During 1 077 299 person-years of follow-up (median follow-up 6.2 years), there were 22 798 CVD events (12 142 in sub-optimal responders and 10 656 in optimal responders). In sub-optimal responders, compared with optimal responders, the HR for incident CVD was 1.17 (95% CI 1.13 to 1.20) and 1.22 (95% CI 1.19 to 1.25) after adjusting for age and baseline untreated LDL-C. Considering competing risks resulted in lower but similar sub-HRs for both unadjusted (1.13, 95% CI 1.10 to 1.16) and adjusted (1.19, 95% CI 1.16 to 1.23) cumulative incidence function of CVD.

          Conclusions

          Optimal lowering of LDL-C is not achieved within 2 years in over half of patients in the general population initiated on statin therapy, and these patients will experience significantly increased risk of future CVD.

          Related collections

          Most cited references15

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          Cardiovascular disease in Europe 2014: epidemiological update.

          This paper provides an update for 2014 on the burden of cardiovascular disease (CVD), and in particular coronary heart disease (CHD) and stroke, across the countries of Europe. Cardiovascular disease causes more deaths among Europeans than any other condition, and in many countries still causes more than twice as many deaths as cancer. There is clear evidence in most countries with available data that mortality and case-fatality rates from CHD and stroke have decreased substantially over the last 5-10 years but at differing rates. The differing recent trends have therefore led to increasing inequalities in the burden of CVD between countries. For some Eastern European countries, including Russia and Ukraine, the mortality rate for CHD for 55-60 year olds is greater than the equivalent rate in France for people 20 years older.
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            Cumulative incidence in competing risks data and competing risks regression analysis.

            T. J. Kim (2007)
            Competing risks occur commonly in medical research. For example, both treatment-related mortality and disease recurrence are important outcomes of interest and well-known competing risks in cancer research. In the analysis of competing risks data, methods of standard survival analysis such as the Kaplan-Meier method for estimation of cumulative incidence, the log-rank test for comparison of cumulative incidence curves, and the standard Cox model for the assessment of covariates lead to incorrect and biased results. In this article, we discuss competing risks data analysis which includes methods to calculate the cumulative incidence of an event of interest in the presence of competing risks, to compare cumulative incidence curves in the presence of competing risks, and to perform competing risks regression analysis. A hypothetical numeric example and real data are used to compare those three methods in the competing risks data analysis to their respective counterparts in the standard survival analysis. The source and magnitude of bias from the Kaplan-Meier estimate is also detailed.
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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

                Journal
                Heart
                Heart
                BMJ
                1355-6037
                1468-201X
                April 15 2019
                : heartjnl-2018-314253
                Article
                10.1136/heartjnl-2018-314253
                51f36410-34f2-4e4b-9b99-40265b8e5225
                © 2019
                History

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