Dataset Information

Optimal Target Level of Low-density Lipoprotein Cholesterol for Vascular Function in Statin Naive Individuals.

ABSTRACT: We investigated (1) the relationship between low-density lipoprotein cholesterol (LDL-C) and vascular function in patients receiving and those not receiving statin therapy and (2) optimal level of LDL-C for maintenance of vascular function. Flow-mediated vasodilation (FMD) and nitroglycerine-induced vasodilation (NID) were inversely correlated with LDL-C in the 957 statin naïve subjects but not in the 392 subjects receiving statin therapy. In statin naïve subjects, non-high LDL-C (?100?mg/dL) was independently associated with a decrease in adjusted odds ratio of the low tertile of FMD (OR: 0.62, 95% CI: 0.45-0.85; P?=?0.003) and NID (OR: 0.69, 95% CI: 0.50-0.96; P?=?0.03). Adjusted odds ratio of the low tertile of FMD was significantly lower in the low LDL-C group (?70?mg/dL) (OR: 0.47, 95% CI, 0.27-0.81; P?=?0.006) and in the moderate LDL-C group (70.1-100?mg/dL) (OR: 0.66, 95% CI, 0.48-0.94; P?=?0.02) than in the high LDL-C group (>100?mg/dL). There was no significant difference in FMD between the low LDL-C group and moderate LDL-C group. There were significant relationships of FMD and NID with LDL-C levels in statin naïve subjects. In a general population, LDL-C of ?100?mg/dL may be the optimal target level for maintenance of endothelial function.

SUBMITTER: Matsui S

PROVIDER: S-EPMC5566450 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimal Target Level of Low-density Lipoprotein Cholesterol for Vascular Function in Statin Naïve Individuals.

Matsui Shogo S Kajikawa Masato M Hida Eisuke E Maruhashi Tatsuya T Iwamoto Yumiko Y Iwamoto Akimichi A Oda Nozomu N Kishimoto Shinji S Hidaka Takayuki T Kihara Yasuki Y Chayama Kazuaki K Goto Chikara C Aibara Yoshiki Y Nakashima Ayumu A Yusoff Farina Binti Mohamad FBM Noma Kensuke K Higashi Yukihito Y

Scientific reports 20170821 1

We investigated (1) the relationship between low-density lipoprotein cholesterol (LDL-C) and vascular function in patients receiving and those not receiving statin therapy and (2) optimal level of LDL-C for maintenance of vascular function. Flow-mediated vasodilation (FMD) and nitroglycerine-induced vasodilation (NID) were inversely correlated with LDL-C in the 957 statin naïve subjects but not in the 392 subjects receiving statin therapy. In statin naïve subjects, non-high LDL-C (≤100 mg/dL) wa ...[more]

PMID: 28827781

Similar Datasets

Project description:BackgroundChemically measured high-density lipoprotein cholesterol (HDL-C) may not be the best clinical measure of HDL. Little is known about alternative HDL measures such as HDL size or particle number (HDL-P) as determinants of residual risk after potent statin therapy.Methods and resultsIn Justification for the Use of statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER), HDL size and HDL-P were measured by nuclear magnetic resonance spectroscopy, and HDL-C and apolipoprotein A-I (apoA-I) were chemically assayed in 10 886 participants without cardiovascular disease (CVD) before and after random allocation to rosuvastatin 20 mg/d or placebo. Levels were examined with first CVD (n=234). HDL-P correlated better with apoA-I (Spearman r=0.69, P<0.0001) than with HDL-C (r=0.55, P<0.0001). Rosuvastatin lowered low-density lipoprotein cholesterol (49%) and raised HDL-C (6.1%), apoA-I (2.1%), HDL-P (3.8%), and HDL size (1.2%); all P<0.0001. Among placebo-allocated individuals, on-treatment HDL-C, apoA-I, and HDL-P had similar inverse associations with CVD (risk factor-adjusted hazard ratio and 95% confidence interval per 1 standard deviation: 0.79 [0.63-0.98], 0.75 [0.62-0.92], and 0.81 [0.67-0.97], respectively). Among rosuvastatin-allocated individuals, on-treatment HDL-P had a statistically significant and somewhat stronger association with CVD (0.73, 0.57-0.93, P=0.01) than HDL-C (0.82, 0.63-1.08, P=0.16) or apoA-I (0.86, 0.67-1.10, P=0.22). Among rosuvastatin-allocated individuals, on-treatment HDL-P remained significant (0.72, 0.53-0.97, P=0.03) after additionally adjusting for HDL-C. In risk factor-adjusted models, HDL size showed no significant association with CVD.ConclusionsIn the setting of potent statin therapy, HDL particle number may be a better marker of residual risk than chemically measured HDL-C or apoA-I. This has potential implications for evaluating novel therapies targeting HDL.Clinical trial registration urlhttp://www.clinicaltrials.gov. Unique identifier: NCT00239681.

Project description:Importance:American College of Cardiology/American Heart Association cholesterol guidelines prioritize primary prevention statin therapy based on 10-year absolute risk (AR10) of atherosclerotic cardiovascular disease (ASCVD). However, given the same AR10, patients with higher levels of low-density lipoprotein cholesterol (LDL-C) experience greater absolute risk reduction from statin therapy. Objectives:To estimate the cost-effectiveness of expanding preventive statin treatment eligibility from standard care to patients at borderline risk (AR10, 5.0%-7.4%) for ASCVD and with high levels of LDL-C and to estimate cost-effectiveness of statin treatment across ranges of age, sex, AR10, and LDL-C levels. Design, Setting, and Participants:This study evaluated 100 simulated cohorts, each including 1 million ASCVD-free survey respondents (50% men and 50% women) aged 40 years at baseline. Cohorts were created by probabilistic sampling of the 1999-2014 US National Health and Nutrition Examination Surveys from the perspective of the US health care sector. The CVD Policy Model microsimulation version projected lifetime health and cost outcomes. Probability of first-ever coronary heart disease or stroke event was estimated by analysis of 6 pooled US cohort studies and recalibrated to match contemporary event rates. Other model variables were derived from national surveys, meta-analyses, and published literature. Data were analyzed from May 15, 2018, through June 10, 2019. Exposures:Four statin treatment strategies were compared: (1) treat all patients with AR10 of at least 7.5%, diabetes, or LDL-C of at least 190 mg/dL (standard care); (2) add treatment for borderline risk and LDL-C levels of 160 to 189 mg/dL; (3) add treatment for borderline risk and LDL-C levels of 130 to 159 mg/dL; and (4) add treatment for remainder of patients with AR10 of at least 5.0%. Statin treatment was also compared with no statin treatment in age, sex, AR10, and LDL-C strata. Main Outcomes and Measures:Lifetime quality-adjusted life-years (QALYs) and costs (2019 US dollars) were projected and discounted 3.0% annually. The primary outcome was the incremental cost-effectiveness ratio. Results:In these 100 simulated cohorts, each with 1 million patients aged 40 years at baseline (50% women and 50% men), adding preventive statins to individuals with borderline AR10 and LDL-C levels of 160 to 189 mg/dL would be cost-saving; further treating borderline AR10 and LDL-C levels of 130 to 159 mg/dL would also be cost-saving; and treating all individuals with AR10 of at least 5.0% would be highly cost-effective ($33?558/QALY) and would prevent the most ASCVD events. Within age, AR10, and sex categories, individuals with higher baseline LDL-C levels gained more QALYs from statin therapy. Cost-effectiveness increased with LDL-C level and AR10. Conclusions and Relevance:In this study, lifetime statin treatment of patients in a hypothetical cohort with borderline ASCVD risk and LDL-C levels of 160 to 189 mg/dL was found to be cost-saving. Results suggest that treating all patients at borderline risk regardless of LDL-C level would likely be highly cost-effective.

Project description:BackgroundAggressive lipid lowering by high-dose statin treatment has been established for the secondary prevention of coronary artery disease (CAD). Regarding the low-density lipoprotein cholesterol (LDL-C) level, however, the "The lower is the better" concept has been controversial to date. We hypothesized that there is an optimal LDL-C level, i.e., a "threshold" value, below which the incidence of cardiovascular events is no longer reduced. We undertook a subanalysis of the REAL-CAD study to explore whether such an optimal target LDL-C level exists by a novel analysis procedure to verify the existence of a monotonic relationship.MethodsFor a total of 11,105 patients with CAD enrolled in the REAL-CAD study, the LDL-C level at 6 months after randomization and 5-year cardiovascular outcomes were assessed. We set the "threshold" value of the LDL-C level under which the hazards were assumed to be constant, by including an artificial covariate max (0, LDL-C - threshold) in the Cox model. The analysis was repeated with different LDL-C thresholds (every 10 mg/dl from 40 to 100 mg/dl) and the model fit was assessed by log-likelihood.ResultsFor primary outcomes such as the composite of cardiovascular death, non-fatal myocardial infarction, non-fatal ischemic stroke, and unstable angina requiring emergency hospitalization, the model fit assessed by log-likelihood was best when a threshold LDL-C value of 70 mg/dl was assumed. And in the model with a threshold LDL-C ≥ 70 mg/dl, the hazard ratio was 1.07 (95% confidence interval 1.01-1.13) as the LDL-C increased by 10 mg/dl. Therefore, the risk of cardiovascular events decreased monotonically until the LDL-C level was lowered to 70 mg/dl, but when the level was further reduced, the risk was independent of LDL-C.ConclusionsOur analysis model suggests that a "threshold" value of LDL-C might exist for the secondary prevention of cardiovascular events in Japanese patients with CAD, and this threshold might be 70 mg/dl for primary composite outcomes.Trial registrationhttp://www.Clinicaltrialsgov . Unique identifier: NCT01042730.

Dataset Information

Optimal Target Level of Low-density Lipoprotein Cholesterol for Vascular Function in Statin Naive Individuals.

Publications

Optimal Target Level of Low-density Lipoprotein Cholesterol for Vascular Function in Statin Naïve Individuals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets