Risk of diabetes in patients treated with HMG-CoA reductase inhibitors

Pharmacophore Modeling and Binding Affinity of Secondary Metabolites from Angelica keiskei to HMG Co-A Reductase

Statins are cholesterol-lowering drugs with a mechanism of inhibiting 3-hydroxy-3-methylglutaryl-CoA reductase, but long-term use can cause side effects. An example of a plant capable of reducing cholesterol levels is Angelica keiskei (ashitaba). Therefore, this study aimed to obtain suitable compounds with inhibitory activity against the HMG-CoA reductase enzyme from ashitaba through in silico tests. The experiment began with screening and pharmacophore modeling, followed by molecular docking on ashitaba's compounds, statins groups, and the native ligand was (3R,5R)-7-[4-(benzyl carbamoyl)-2-(4-fluorophenyl)-5-(1-methylethyl)-1H-imidazole-1-yl]-3,5-dihydroxyheptanoic acid (4HI). Based on the results of the molecular docking simulations, 15 hit compounds had a small binding energy (ΔG). Pitavastatin, as the comparator drug (ΔG = -8.24 kcal/mol; Ki = 2.11 µM), had a lower ΔG and inhibition constant (Ki) than the native ligand 4HI (ΔG = -7.84 kcal/mol; Ki = 7.96µM). From ashitaba's compounds, it was found that 4'-O-geranylnaringenin, luteolin, isobavachalcone, dorsmannin A, and 3'-carboxymethyl-4,2'-dihydroxy-4'-methoxychalcone have low ΔG of below -6 kcal/mol. The lowest ΔG value was found in 3'-carboxymethyl-4,2'-dihydroxy-4'-methoxy chalcone with a ΔG of -6.67 kcal/mol and Ki value of 16.66 µM, which was lower than the ΔG value of the other comparator drugs, atorvastatin (ΔG = -5.49 kcal/mol; Ki = 1148.17 µM) and simvastatin (ΔG = -6.50 kcal/mol; Ki = 22.34 µM). This compound also binds to the important amino acid residues, including ASN755D, ASP690C, GLU559D, LYS735D, LYS691C, and SER684C, through hydrogen bonds. Based on the results, the compound effectively binds to six important amino acids with good binding affinity and only requires a small concentration to reduce half of the enzyme activity.

Statins and new-onset diabetes in primary prevention setting: an updated meta-analysis stratified by baseline diabetes risk

AIMS

The use of statins has been associated with an increased risk of new-onset diabetes. The characteristics of the population could influence this association. The objective of this study was to determine the risk of new-onset diabetes with the use of statins in patients in primary prevention, with an assessment of the results according to the baseline risk of developing diabetes of the included population.

METHODS

We performed an updated meta-analysis including randomized trials of statin therapy in primary prevention settings that report new-onset diabetes. The rate of new cases of diabetes in the control arms was estimated for each study. The studies were classified into two groups (low rate: < 7.5 events per 1000 patients-year; high rate; ≥ 7.5 events per 1000 patients-year). The fixed-effects model was performed.

RESULTS

Eight studies (70,453 patients) were included. Globally, statin therapy was associated with an increased risk of new-onset diabetes (OR 1.1; 95% CI 1.0-1.2, I2 35%). When we analyzed the studies according to the baseline diabetes risk in the control groups, the results showed that there was a greater risk only in the studies with a high baseline rate (OR 1.2; 95% CI 1.1-1.3, I2 0%; interaction p value = 0.01).

CONCLUSION

Globally, the use of statins in patients in primary prevention was associated with an increased risk of new-onset diabetes. In the stratified analysis, this association was observed only in the group of studies with a high baseline rate of events.

Novel Therapeutic Agents for Management of Diabetes Mellitus: A Hope for Drug Designing against Diabetes Mellitus

Diabetes mellitus (DM) is characterized by an absolute decline in insulin secretion and peripheral resistance and is the most prevalent metabolic and endocrine disorder. However, the pathogenesis of DM also includes adipocyte insulin resistance, increased glucagon secretion, increased renal glomerular glucose absorption, and neurotransmitter dysfunction. Although there is a wide spectrum of therapeutics available for glycemic control, owing to the identification of various pathogenic determinants of DM, management of DM remains challenging and complex. Current therapeutic interventions against DM focus mostly on glycemic control without considering the other pathological determinants that eventually lead to treatment failure and the progression of DM. Furthermore, long-term use of these conventionally available anti-diabetic drugs leads to various side effects, henceforth development of novel drugs against DM remains an unending search strategy for researchers. Various studies conducted in various parts of the world have proposed that these novel therapeutic interventions target multiple and alternate pathogenic hotspots involved in DM. The current review article discusses novel therapeutic options that hold particular promise to support their safety and discuss the side effects resulting from their use so that these novel candidate drugs can be effectively fabricated into potential drugs for the treatment of DM.

Learning and visualizing chronic latent representations using electronic health records

Background

Nowadays, patients with chronic diseases such as diabetes and hypertension have reached alarming numbers worldwide. These diseases increase the risk of developing acute complications and involve a substantial economic burden and demand for health resources. The widespread adoption of Electronic Health Records (EHRs) is opening great opportunities for supporting decision-making. Nevertheless, data extracted from EHRs are complex (heterogeneous, high-dimensional and usually noisy), hampering the knowledge extraction with conventional approaches.

Methods

We propose the use of the Denoising Autoencoder (DAE), a Machine Learning (ML) technique allowing to transform high-dimensional data into latent representations (LRs), thus addressing the main challenges with clinical data. We explore in this work how the combination of LRs with a visualization method can be used to map the patient data in a two-dimensional space, gaining knowledge about the distribution of patients with different chronic conditions. Furthermore, this representation can be also used to characterize the patient’s health status evolution, which is of paramount importance in the clinical setting.

Results

To obtain clinical LRs, we considered real-world data extracted from EHRs linked to the University Hospital of Fuenlabrada in Spain. Experimental results showed the great potential of DAEs to identify patients with clinical patterns linked to hypertension, diabetes and multimorbidity. The procedure allowed us to find patients with the same main chronic disease but different clinical characteristics. Thus, we identified two kinds of diabetic patients with differences in their drug therapy (insulin and non-insulin dependant), and also a group of women affected by hypertension and gestational diabetes. We also present a proof of concept for mapping the health status evolution of synthetic patients when considering the most significant diagnoses and drugs associated with chronic patients.

Conclusion

Our results highlighted the value of ML techniques to extract clinical knowledge, supporting the identification of patients with certain chronic conditions. Furthermore, the patient’s health status progression on the two-dimensional space might be used as a tool for clinicians aiming to characterize health conditions and identify their more relevant clinical codes.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13040-022-00303-z).

Impact of pitavastatin on new-onset diabetes mellitus compared to atorvastatin and rosuvastatin: a distributed network analysis of 10 real-world databases

BACKGROUND

Statin treatment increases the risk of new-onset diabetes mellitus (NODM); however, data directly comparing the risk of NODM among individual statins is limited. We compared the risk of NODM between patients using pitavastatin and atorvastatin or rosuvastatin using reliable, large-scale data.

METHODS

Data of electronic health records from ten hospitals converted to the Observational Medical Outcomes Partnership Common Data Model (n = 14,605,368 patients) were used to identify new users of pitavastatin, atorvastatin, or rosuvastatin (atorvastatin + rosuvastatin) for ≥ 180 days without a previous history of diabetes or HbA1c level ≥ 5.7%. We conducted a cohort study using Cox regression analysis to examine the hazard ratio (HR) of NODM after propensity score matching (PSM) and then performed an aggregate meta-analysis of the HR.

RESULTS

After 1:2 PSM, 10,238 new pitavastatin users (15,998 person-years of follow-up) and 18,605 atorvastatin + rosuvastatin users (33,477 person-years of follow-up) were pooled from 10 databases. The meta-analysis of the HRs demonstrated that pitavastatin resulted in a significantly reduced risk of NODM than atorvastatin + rosuvastatin (HR 0.72; 95% CI 0.59-0.87). In sub-analysis, pitavastatin was associated with a lower risk of NODM than atorvastatin or rosuvastatin after 1:1 PSM (HR 0.69; CI 0.54-0.88 and HR 0.74; CI 0.55-0.99, respectively). A consistently low risk of NODM in pitavastatin users was observed when compared with low-to-moderate-intensity atorvastatin + rosuvastatin users (HR 0.78; CI 0.62-0.98).

CONCLUSIONS

In this retrospective, multicenter active-comparator, new-user, cohort study, pitavastatin reduced the risk of NODM compared with atorvastatin or rosuvastatin.

Mini-Review on the efficacy and safety of pitavastatin: “The novel seventh statin gaining momentum”

Background:

Recently, a plethora of events have affected the statin arena such as muscle-induced myalgia, myopathy, myositis, rare rhabdomyolysis, and new-onset diabetes. The latest statin pitavastatin has emerged with descent stamina (optimum efficacy and improved safety).

Objective:

The objective of the current review is to explore the pros and cons of pitavastatin as a novel second-generation statin in terms of efficacy and safety that delineate its clinical utility.

Methods:

The review was conducted via EBSCO hosted Medline search (AL Ain University, UAE subscription) for relevant English written literature articles containing “pitavastatin” as the primary search term “pitavastatin and safety;” “pitavastatin and efficacy” and “pitavastatin and safety and randomized clinical trials;” and “pitavastatin and efficacy and randomized clinical trials.”

Results:

The number of articles containing the word “pitavastatin” as the primary search term used was (n = 901). The next retrieves MeSH term was “pitavastatin and safety” (n = 99) and then “pitavastatin and efficacy” (n = 132). Furthermore, narrowing down the search by adding study design terms revealed: “pitavastatin and safety and randomized clinical trials,” (n = 10) and “pitavastatin and efficacy and randomized clinical trials” (n = 13). Combining the two main searches (safety and efficacy) has yielded 23 items, of which 15 articles were satisfying the current mini-review criteria. The prominent efficacy of pitavastatin was depicted by the increase in high-dense lipoprotein cholesterol and a decrease in low-dense lipoprotein cholesterol as illustrated by the clinical trials in the results and discussions section. The safety was enlightened with a very low propensity to cause new-onset diabetes and a low tendency for statin-induced muscular adverse events.

Conclusion:

Pitavastatin might be suitable for patients with the acute coronary syndrome (ACS), metabolic syndrome, and patients with diabetes. We highly recommend rational individualization for the selection of statin, especially in patients with diabetes and/or with ACS.

Interpreting clinical latent representations using autoencoders and probabilistic models

Electronic health records (EHRs) are a valuable data source that, in conjunction with deep learning (DL) methods, have provided important outcomes in different domains, contributing to supporting decision-making. Owing to the remarkable advancements achieved by DL-based models, autoencoders (AE) are becoming extensively used in health care. Nevertheless, AE-based models are based on nonlinear transformations, resulting in black-box models leading to a lack of interpretability, which is vital in the clinical setting. To obtain insights from AE latent representations, we propose a methodology by combining probabilistic models based on Gaussian mixture models and hierarchical clustering supported by Kullback-Leibler divergence. To validate the methodology from a clinical viewpoint, we used real-world data extracted from EHRs of the University Hospital of Fuenlabrada (Spain). Records were associated with healthy and chronic hypertensive and diabetic patients. Experimental outcomes showed that our approach can find groups of patients with similar health conditions by identifying patterns associated with diagnosis and drug codes. This work opens up promising opportunities for interpreting representations obtained by the AE-based model, bringing some light to the decision-making process made by clinical experts in daily practice.

Use of Network Pharmacology to Explore the Mechanism of Gegen (Puerariae lobatae Radix) in the Treatment of Type 2 Diabetes Mellitus Associated with Hyperlipidemia

Rapid increases in metabolic disorders, such as type 2 diabetes mellitus (T2DM) and hyperlipidemia, are becoming a substantial challenge to worldwide public health. Traditional Chinese medicine has a long history and abundant experience in the treatment of diabetes and hyperlipidemia, and Puerariae lobatae Radix (known as Gegen in Chinese) is one of the most prevalent Chinese herbs applied to treat these diseases. The underlying mechanism by which Gegen simultaneously treats diabetes and hyperlipidemia, however, has not been clearly elucidated to date. Therefore, we systematically explored the potential mechanism of Gegen in the treatment of T2DM complicated with hyperlipidemia based on network pharmacology. We screened the potential targets of Gegen, T2DM, and hyperlipidemia in several online databases. Then, the hub targets were analyzed by performing protein-protein interaction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment assays, and finally, the complicated connections among compounds, targets, and pathways were visualized in Cytoscape. We found that isoflavones, including daidzein, genistein, and puerarin, as well as β-sitosterol, are the key active ingredients of Gegen responsible for its antidiabetic and antihyperlipidemia effects, which mainly target AKR1B1, EGFR, ESR, TNF, NOS3, MAPK3, PPAR, CYP19A1, INS, IL6, and SORD and multiple pathways, such as the PI3K-Akt signaling pathway; the AGE-RAGE signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis; the PPAR signaling pathway; insulin resistance; the HIF-1 signaling pathway; the TNF signaling pathway; and others. These active ingredients also target multiple biological processes, including the regulation of glucose and lipid metabolism, the maintenance of metabolic homeostasis, and anti-inflammatory and antioxidant pathways. In conclusion, Gegen is a promising therapeutic phytomedicine for T2DM with hyperlipidemia that targets multiple proteins, biological processes, and pathways.

Effects of Pitavastatin, Atorvastatin, and Rosuvastatin on the Risk of New-Onset Diabetes Mellitus: A Single-Center Cohort Study

Statins constitute the mainstay treatment for atherosclerotic cardiovascular disease, which is associated with the risk of new-onset diabetes mellitus (NODM). However, the effects of individual statins on the risk of NODM remain unclear. We recruited 48,941 patients taking one of the three interested statins in a tertiary hospital between 2006 and 2018. Among them, 8337 non-diabetic patients taking moderate-intensity statins (2 mg/day pitavastatin, 10 mg/day atorvastatin, and 10 mg/day rosuvastatin) were included. The pitavastatin group had a higher probability of being NODM-free than the atorvastatin and rosuvastatin groups during the 4-year follow-up (log-rank test: p = 0.038). A subgroup analysis revealed that rosuvastatin had a significantly higher risk of NODM than pitavastatin among patients with coronary artery disease (CAD) (adjusted HR [aHR], 1.47, 95% confidence interval [CI], 1.05–2.05, p = 0.025), hypertension (aHR, 1.26, 95% CI, 1.00–1.59, p = 0.047), or chronic obstructive pulmonary disease (COPD) (aHR, 1.74, 95% CI, 1.02–2.94, p = 0.04). We concluded that compared with rosuvastatin, reduced diabetogenic effects of pitavastatin were observed among patients treated with moderate-intensity statin who had hypertension, COPD, or CAD. Additional studies are required to prove the effects of different statins on the risk of NODM.

Safety and Efficacy of Pitavastatin in Patients With Impaired Fasting Glucose and Hyperlipidemia: A Randomized, Open-labeled, Multicentered, Phase IV Study

PURPOSE

Although the role of high-intensity lipid-lowering therapy in cardiovascular protection has broadened, concerns still exist about new-onset diabetes mellitus (NODM), especially in vulnerable patients. This study aimed to compare the effect of high-dose (4 mg/d) and usual dose (2 mg/d) pitavastatin on glucose metabolism in patients with hyperlipidemia and impaired fasting glucose (IFG).

METHODS

In this 12-month study, glucose tolerance and lipid-lowering efficacy of high-dose pitavastatin (4 mg [study group]) was compared with that of usual dose pitavastatin (2 mg [control group]) in patients with hyperlipidemia and IFG. The primary end point was the change of glycosylated hemoglobin (HbA_1c) after 24 weeks of treatment. The secondary end points were as follows: (1) NODM within 1 year after treatment, (2) change of lipid parameters, (3) changes of adiponectin, and (4) change of blood glucose and insulin levels.

FINDINGS

Of the total 417 patients screened, 313 patients with hypercholesterolemia and IFG were randomly assigned into groups. The mean (SD) change in HbA_1c was 0.06% (0.20%) in the study group and 0.03% (0.22%) in the control group (P = 0.27). Within 1 year, 27 patients (12.3%) developed NODM, including 12 (10.6%) of 113 patients in the study group and 15 (14.2%) of 106 in the control group (P = 0.43). The study group had a significantly higher reduction of total cholesterol and LDL-C levels and a higher increase in apolipoprotein A1/apolipoprotein B ratio (0.68 [0.40] vs 0.51 [0.35], P < 0.01).

IMPLICATIONS

The high-dose pitavastatin therapy did not aggravate glucose metabolism compared with the usual dose therapy. Moreover, it had a better effect on cholesterol-lowering and apolipoprotein distribution in the patients with hyperlipidemia and IFG.

Statin use increased new-onset diabetes in hypercholesterolemic individuals: Data from the Korean National Health Insurance Service-National Health Screening Cohort database (NHIS-HEALS)

AIM

We investigated the association between statin use and new-onset diabetes (NODM) in Korean adults with hypercholesterolemia.

METHODS

This study performed based on data from the National Health Insurance Service-National Health Screening Cohort for the years from 2002 to 2015. Statin users classified as high- or low- users according to medication possession ratio. Statin non-users consisted of hypercholesterolemic participants who never used statin over the entire follow-up period. 21,469 participants (10,880 statin users, 10,589 statin non-users) with a median follow-up period of 12.5 years were included. We estimated the NODM risk based on the survival analyses. In particular, to adjust for confounding effects, we considered Cox proportional hazards regression models over three stages.

RESULTS

Compared to non-users, statin users had a significantly higher risk for NODM. The fully adjusted hazard ratios (aHRs) (95% confidential intervals [95% CIs]) of statin users for NODM were 1.43 (1.31-1.57) in men, and 1.86 (1.66-2.10) in women, respectively after adjusted confounding factors including age and lifestyle factors. Compared to high-users, aHRs (95% CIs) of low-users for NODM were 1.16 (1.03-1.30) and 1.28 (1.16-1.43) in men and women, respectively.

CONCLUSIONS

In hypercholesterolemic patients, statin users have a higher risk of NODM than non-users.

Time-varying and dose-dependent effect of long-term statin use on risk of type 2 diabetes: a retrospective cohort study

BACKGROUND

We evaluated the effect of statin use on new-onset type 2 diabetes among individuals without atherosclerotic cardiovascular disease (ASCVD) using nationally representative South Korean claims data (2002-2013, N = 1,016,820).

METHODS

A total of 13,698 patients (statin users 5273, non-statin users 5273) aged 40-74 years, newly diagnosed with dyslipidemia but without any history of diabetes or ASCVD, were selected in 2005. We followed up the final sample until 2013 and evaluated the cumulative incidence of type 2 diabetes. We used extended Cox regression models to estimate the time-varying adjusted hazard ratios of statin use on new-onset type 2 diabetes. We performed further analyses based on the cumulative defined daily dose of statin received per year to evaluate the degree of risk compared to non-statin users.

RESULTS

Over the mean follow-up period of 7.1 years, 3034 patients developed type 2 diabetes; the number of statin users exceeded that of non-users, demonstrating that statin use significantly increased the risk of new-onset type 2 diabetes. The risk of new-onset type 2 diabetes differed among statin users according to cDDD per year (adjusted HR = 1.31 [95% CI 1.18-1.46] for less than 30 cDDD per year; 1.58 [1.43-1.75] for 30-120 cDDD per year; 1.83 [1.62-2.08] for 120-180 cDDD per year; and 2.83 [2.51-3.19] for more than 180 cDDD per year). The diabetogenic effect of pitavastatin was not statistically significant, but the risk was the largest for atorvastatin. Long-term exposure (≥ 5 years) to statins was associated with a statistically significant increase in the risk of new onset type 2 diabetes in all statin subtypes explored, with the highest magnitude for simvastatin (HR = 1.916, 95% CI 1.647-2.228) followed by atorvastatin (HR = 1.830, 95% CI 1.487-2.252).

CONCLUSIONS

Statin use was significantly associated with an increased risk of new-onset type 2 diabetes. We also found a dose-response relationship in terms of statin use duration and dose maintenance. Periodic screening and monitoring for incident type 2 diabetes may be warranted in long-term statin users.

The Pleiotropic Effects of Statins in Endocrine Disorders

BACKGROUND

The 3-Hydroxy-3-MethylGlutaryl-CoA reductase inhibitors, better known as statins, are used extensively in the treatment of dyslipidemia and cardiovascular risk reduction. They have also demonstrated a variety of non-lipid lowering, or pleiotropic effects. Pertaining to the endocrine system the benefits of statins can extend to patients with the polycystic ovarian syndrome and thyroid disease. However, there is also increasing evidence that statin use can lead to deleterious effects in different organs, including worsening glycemia and the development of diabetes mellitus.

OBJECTIVE

The aim of this review is to describe the most relevant and updated evidence regarding the pleiotropic effects of statins in endocrine disorders.

METHODS

We did a systematic review of scientific articles published in PubMed regarding the effects of statins on the different aspects of the endocrine system up until June 5th of 2018.

RESULTS

We identified preliminarily 61 publications, of which 4 were excluded due to having abstract format only, and 5 were excluded for not containing pertinent information to the study.

CONCLUSION

Several aspects of the endocrine system have been shown to be influenced by the pleiotropic effects that statins exert, however, the benefits of statins on cardiovascular morbidity and mortality largely outweigh this deleterious effect, and statin therapy should continue to be recommended.

Assessment of effect modification of statins on new-onset diabetes based on various medical backgrounds: a retrospective cohort study

BACKGROUND

The aim of this study was to investigate the association between statin use and new-onset diabetes in clinical settings and to assess its effect modification (heterogeneity) among patients with various medical histories and current medications.

METHODS

In a total of 12,177 Japanese patients without diabetes, from December 2004 to November 2012, we identified 500 statin users and 500 matched non-users using propensity-score matching. Patients were followed until December 2017. We estimated the hazard ratios of new-onset diabetes associated with statin use. We also tested the heterogeneity of the treatment effect by evaluating subgroup interactions in subgroups according to sex, age, medical history, and current medication.

RESULTS

New-onset diabetes had occurred in 71 patients (13.6%) with statin use and 43 patients (8.3%) with non-use at 5 years (hazard ratio, 1.66; 95% confidence interval [CI], 1.11 to 2.48; P = 0.0143), and in 78 patients (15.6%) with statin use and 48 patients (9.6%) with non-use at 10 years (hazard ratio, 1.61; 95% CI, 1.10 to 2.37; P = 0.0141). There were no significant treatment-by-subgroup interactions in all subgroups defined according to sex, age, medical history, and current medication.

CONCLUSIONS

In patients with various clinical backgrounds, those who received statin therapy had a higher risk of new-onset diabetes at 5 and 10 years than those who did not receive it. Effect modification of statins on new-onset diabetes was not found in patient populations defined according to various comorbid diseases or concomitant drugs.

Effects of statin exposure and lung cancer survival: A meta-analysis of observational studies

Statin exposure has been reported to improve survival in several cancers. However, studies evaluating the association between statins and prognostic outcomes in patients with lung cancer are conflicting and heterogeneous. Pubmed, EMBASE and reference lists of included studies were searched to identify studies investigating the association between statin exposure and lung cancer prognosis. The primary outcome measure was overall survival (OS) and secondary ones included cancer-specific survival (CSS) and recurrence-free survival (RFS). Hazard ratios (HRs) with 95% confidence intervals (95% CIs) of these outcomes were pooled using random-effects models. Thirteen studies with data from 99,297 individuals satisfying the inclusion criteria were identified. Studies were ranked to be at low to moderate risk of bias. Meta-analysis showed that statin exposure was significantly associated with improved OS (pooled HR 0.79, 95% CI 0.72-0.86), CSS (pooled HR 0.83, 95% CI 0.77-0.89) and RFS (pooled HR 0.85, 95% CI 0.81-0.89). Subgroup analyses showed that statin users after diagnosis of lung cancer had more survival benefit for OS (HR 0.68, 95% CI 0.51-0.92) than those before diagnosis (HR 0.86, 95% CI 0.81-0.90) and current users (HR 0.79, 95% CI 0.62-1.02) (P for interaction <0.001). Besides, statin users were likely to have more survival benefits in stage IV lung cancer patients (HR 0.77, 95% CI 0.74-0.79) than in mixed stage (I-IV or I-III) patients (P for interaction = 0.004). Statin exposure is associated with significantly improved survival in patients with lung cancer. Future studies are warranted to further demonstrate the therapeutic role of statins in specific lung cancer patients.

Association between statin treatment and new-onset diabetes mellitus: a population based case-control study

BACKGROUND

Several studies suggest that statin may increase the risk of new-onset diabetes mellitus (NODM). This study aimed to evaluate the association between the duration and recent use of statin, and the risk of NODM, based on population-based data sets.

METHODS

We used the South Korean National Health Insurance Service National Sample Cohort database for this nationwide case-control study. Of the 1 million participants, 6417 participants with NODM in 2012-2013 and 32,085 controls without diabetes (1:5 propensity score matched with age, sex, index year, and year of diabetes diagnosis) were included. In these patients, we examined the statin prescription record for 3 years preceding the outcome. We used conditional logistic regression to calculate the odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

After adjustment of covariates, there were no significant differences in the risk of NODM when analyzed according to cumulative use days. The risk of NODM was increased only in the short-term and recent user group (OR 1.48, 95% CI 1.21 to 1.82) whose cumulative prescription days are less than 6 months and whose last prescription is within 6 months of diagnosis.

CONCLUSIONS

The risk of NODM was not associated with an increase in the cumulative duration of statin use or with non-recent use. Only recent short-term use of statin was associated with an increased risk of NODM. Diabetes screening are warranted during initial statin therapy.

Effect of statins on fasting glucose in non-diabetic individuals: nationwide population-based health examination in Korea

BACKGROUND

Increasing evidence suggest that statin therapy has a diabetogenic effect. Individual types of statin may have a different effect on glucose metabolism. Using the repeated nationwide population-based health screening data in Korea, we investigated the longitudinal changes in fasting glucose level of non-diabetic individuals by use of statins.

METHODS

From the National Health Screening Cohort, we included 379,865 non-diabetic individuals who had ≥ 2 health screening examinations with fasting blood glucose level measured in 2002-2013. Using the prescription records of statins in the database, we calculated the proportion of days covered (PDC) and average number of defined daily doses per day (anDDD) by statins. We constructed multivariate linear mixed models to evaluate the effects of statins on the changes in fasting glucose (Δglu).

RESULTS

High PDC by statins had a significant positive effect on Δglu (coefficient for PDC 0.093 mmol/L, standard error 0.007, p < 0.001). anDDD by statins was also positively associated with Δglu (coefficient for anDDD 0.119 mmol/L, standard error 0.009, p < 0.001). Unlike statins, the PDC by fibrate and ezetimibe were not significantly associated with Δglu. There was no significant interaction effect on Δglu between time interval and statin. Considering individual types of statins, use of atorvastatin, rosuvastatin, pitavastatin, and simvastatin were significantly associated with increase of Δglu. Pravastatin, lovastatin, and fluvastatin were also positively associated with Δglu, but were not statistically significant.

CONCLUSIONS

More adherent and intensive use of statins was significantly associated with an increase in fasting glucose of non-diabetic individuals. In subgroup analysis of individual statins, use of atorvastatin, rosuvastatin, pitavastatin and simvastatin had significant association with increase in fasting glucose. Pravastatin, lovastatin, and fluvastatin had non-significant trend toward an increased fasting glucose. Our findings suggest the medication class effect of statins inducing hyperglycemia.

Effects of Pitavastatin on Insulin Sensitivity and Liver Fat: A Randomized Clinical Trial

Context

3-Hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors (statins) are widely prescribed. Statins may have important metabolic effects on insulin sensitivity and liver fat, but limited studies have assessed these effects by using euglycemic hyperinsulinemic clamp, stable isotopes, and 1H magnetic resonance spectroscopy (MRS) for liver fat quantification.

Objective

To study the effects of pitavastatin on hepatic fat and insulin sensitivity.

Design

Six-month, double-blind, randomized, placebo-controlled trial.

Setting

Academic clinical research center in Boston, Massachusetts.

Participants

Overweight, insulin-resistant men aged 40 to 65 years who had not received statin therapy for ≥1 year.

Interventions

Pitavastatin 4 mg or placebo daily.

Outcome

The primary endpoints were changes in insulin sensitivity measured by euglycemic hyperinsulinemic clamp and liver fat measured by 1H MRS.

Results

Pitavastatin showed no effect on endogenous glucose production (ΔRa glucose 0.07 ± 0.07 vs 0.04 ± 0.07 mg/kg/min, pitavastatin vs placebo, P = 0.76) or insulin-stimulated glucose uptake during "low dose" (ΔM 0.1 ± 0.1 vs -0.3 ± 0.2 mg/kg/min, P = 0.11) and "high dose" (ΔM -0.5 ± 0.3 vs -0.7 ± 0.4 mg/kg/min, P = 0.70) euglycemic hyperinsulinemic clamps. There was also no effect of pitavastatin on fasting glucose, HbA1c, and 2-hour glucose after 75-g glucose challenge. There was also no change in liver fat fraction (-1 ± 1 vs -0 ± 1%, P = 0.56).

Conclusion

Compared with placebo, pitavastatin did not affect hepatic or whole-body insulin sensitivity, and it did not reduce liver fat.

Is Atorvastatin Associated with New Onset Diabetes or Deterioration of Glycemic Control? Systematic Review Using Data from 1.9 Million Patients

BACKGROUND

Current evidence indicates that statins increase the risk of new onset diabetes mellitus (NOD) and also deteriorate the glycemic control in patients with known diabetes mellitus (DM) after high-dose statin therapy.

AIMS

The aim of this review was to explore the effect of atorvastatin in causing NOD or deteriorating glycemic control in patients with DM.

METHODS

Two independent reviewers conducted the literature search, through PubMed database searching for articles published in English until April 2015, and only primary studies were included.

RESULTS

Of the 919 articles identified in our original search, 33 met the criteria for this review encompassing 1,951,113 participants. Twenty articles examined dysregulation of DM due to atorvastatin. Half of them showed that there was no significant change in glycemic control in patients treated with atorvastatin. Other studies showed that fasting plasma glucose and HbA1c levels were increased by atorvastatin. Thirteen articles examined if atorvastatin causes NOD. The majority of these articles showed that patients who used atorvastatin had a higher dose-dependent risk of developing NOD.

CONCLUSION

This systematic review suggests that there is an association between atorvastatin treatment and NOD. Moreover, it showed that atorvastatin in high dose causes worsening of the glycemic control in patients with DM.

A Multi-Center, Open-Label, Two-Arm Parallel Group Non-inferiority Randomized Controlled Trial Evaluating the Effect of Pitavastatin, Compared to Atorvastatin, on Glucose Metabolism in Prediabetics with Hypertension and Dyslipidemia: Rationale and Design for the China Hemoglobin A1c Metabolism Protection Union Study (CAMPUS)

BACKGROUND

Hypertension and dyslipidemia are major risk factors for cardiovascular disease (CVD). In 2012, over 270 million patients (25.2%) in China were hypertensive and 40.4% was dyslipidemic. The majority of these patients rely on statins for the prevention of cardiovascular disease. However, certain types of statins (e.g., atorvastatin), compared to others (e.g., pitavastatin), may be associated with unfavorable effects on glucose metabolism. This leads to concerns when prescribing statins to patients who also have a predisposition to glucose metabolic disorders (i.e., prediabetes). Thus, this study aims to investigate the effect of pitavastatin, compared to atorvastatin, on glucose metabolism, as measured by hemoglobin A1c (HbA1c), in Chinese prediabetics with hypertension and dyslipidemias.

METHODS

The China hemoglobin A1c Metabolism Protection Union Study (CAMPUS) is a multi-center, prospective, open-label, 12-month, two-arm parallel group, and non-inferiority randomized controlled trial (RCT). A total of 396 prediabetics with hypertension and dyslipidemias will be randomly assigned 1:1 to either pitavastatin 2 mg/day or atorvastatin 20 mg/day, and followed for 12 months (follow-up visits at 1, 3, 6, and 12 months) for HbA1c levels, as well as other measures of glucose metabolism, serum lipid levels, blood pressure control, measures of inflammation, vascular endothelial function, carotid atherosclerosis, and hypertension-related left ventricular hypertrophy. If the results of low-density lipoprotein cholesterol (LDL-C) levels in month 3 after treatment initiation do not meet individual target, drug dose for the participant would be doubled.

DISCUSSION

CAMPUS will be the first RCT to investigate the effect of pitavastatin, compared to atorvastatin, on glucose metabolism in Chinese prediabetics with hypertension and dyslipidemias. Further, this study might eventually provide information to design a clinical strategy, and facilitate the improvement of primary prevention in patients at risk for diabetes and CVD.

TRIAL REGISTRATION

ClinicalTrials.gov number: NCT03532620. Registered 22 May 2018.

The Anti-Inflammatory Effects of Statins on Coronary Artery Disease: An Updated Review of the Literature

Background:

Statins have long been used for the protection against coronary artery disease (CAD). Their beneficial effect apart from cholesterol reduction lies in their pleiotropic properties. Emerging evidence from laboratory studies and clinical trials as well have pointed out the pivotal role of inflammation on the initiation and exacerbation of atherosclerosis; a major cause of CAD. Inflam-mation markers such as high sensitivity C-reactive protein and adhesion molecules are shown to in-crease in CAD patients and are used as prognostic tools. It is well known that statins can actually re-duce the circulating levels of these agents slowing therefore the inflammatory process; interestingly not all types have the same outcome.

Conclusion:

The anti-inflammatory effect of statins on the formation of atherosclerotic plaque and the function of endothelial cells is thus of particular importance as these agents can actually ameliorate CAD prognosis

The differences in the incidence of diabetes mellitus and prediabetes according to the type of HMG-CoA reductase inhibitors prescribed in Korean patients

BACKGROUND

Very few studies conducted in Korea have investigated the relationship between statins and the incidence of diabetes. Therefore, we analyzed the progression from normal blood glucose to prediabetes and then to diabetes mellitus (DM) according to the type, intensity, and dose of statin prescribed.

METHODS

Data of patients who were first prescribed statins between 2009 and 2011 were extracted from electronic medical records. Patients with normal blood glucose or prediabetes were observed for 4 years after initiation of statin therapy.

RESULTS

A total of 2890 patients were included in our study and analyzed on the basis of the first statin they were prescribed. The incidence rate of DM in patients with prediabetes was 1.72 times that of patients with normal glucose levels (odds ratio = 1.72, 95% confidence interval = 1.41-2.10, P < .001). Regarding progression from normal blood glucose to prediabetes, the incidence rate of prediabetes was significantly lower in patients prescribed pitavastatin (odds ratio = 0.62, 95% confidence interval = 0.40-0.96, P = .031) compared to that in patients prescribed atorvastatin. Regarding the progression from normal blood glucose or prediabetes to DM, there were no significant differences among all statins.

CONCLUSIONS

Lower DM incidence in patients prescribed pitavastatin appears to be primarily because of the lower rate of progression from normal blood glucose to prediabetes. These findings indicate that avoiding statins because of DM risk is unjustified and that clinicians should prescribe statins from the appropriate potency group.

2017 Position Paper of the Italian Society for Cardiovascular Prevention (SIPREC) for an Updated Clinical Management of Hypercholesterolemia and Cardiovascular Risk: Executive Document

The benefits achieved by implementing cardiovascular prevention strategies in terms of reduced incidence of atherosclerotic diseases and mortality are accepted, worldwide. In particular, the clinical management of hypercholesterolemia has a fundamental role for all preventive strategies, both in primary and secondary prevention, at each stage of cardiovascular risk. Since the net clinical benefit of lipid-lowering therapy largely depends on baseline individual cardiovascular risk profile, the assessment of individual risk is essential to establish type and intensity of both preventive and therapeutic strategies. Thus, the real challenge in a setting of clinical practice is not only to identify whom to treat among individuals at low-to-moderate risk, but mostly how much and how long to treat high or very-high risk patients. This manuscript, which reflects concepts and positions that have been published in a more extensive document of the Italian Society for Cardiovascular Prevention (SIPREC), deals with the diagnostic and therapeutic management of patients with dyslipidaemia, with an evidence-based approach adapted and updated from recent guidelines of the European Society of Cardiology and very recent results of randomized clinical trials. The purpose is to suggest a multidimensional and integrated actions aimed at eliminating or minimizing the impact of cardiovascular diseases and their related disabilities and mortality in patients with hypercholesterolemia.

Development of Clinical Data Mart of HMG-CoA Reductase Inhibitor for Varied Clinical Research

BACKGROUND

The increasing use of electronic medical record (EMR) systems for documenting clinical medical data has led to EMR data being increasingly accessed for clinical trials. In this study, a database of patients who were prescribed statins for the first time was developed using EMR data. A clinical data mart (CDM) was developed for cohort study researchers.

METHODS

Seoul St. Mary's Hospital implemented a clinical data warehouse (CDW) of data for ~2.8 million patients, 47 million prescription events, and laboratory results for 150 million cases. We developed a research database from a subset of the data on the basis of a study protocol. Data for patients who were prescribed a statin for the first time (between the period from January 1, 2009 to December 31, 2015), including personal data, laboratory data, diagnoses, and medications, were extracted.

RESULTS

We extracted initial clinical data of statin from a CDW that was established to support clinical studies; the data was refined through a data quality management process. Data for 21,368 patients who were prescribed statins for the first time were extracted. We extracted data every 3 months for a period of 1 year. A total of 17 different statins were extracted. It was found that statins were first prescribed by the endocrinology department in most cases (69%, 14,865/21,368).

CONCLUSION

Study researchers can use our CDM for statins. Our EMR data for statins is useful for investigating the effectiveness of treatments and exploring new information on statins. Using EMR is advantageous for compiling an adequate study cohort in a short period.

Pharmacometabolomic signature links simvastatin therapy and insulin resistance

Introduction

Statins, widely prescribed drugs for treatment of cardiovascular disease, inhibit the biosynthesis of low density lipoprotein cholesterol (LDL-C). Despite providing major benefits, sub populations of patients experience adverse effects, including muscle myopathy and development of type II diabetes mellitus (T2DM) that may result in premature discontinuation of treatment. There are no reliable biomarkers for predicting clinical side effects in vulnerable individuals. Pharmacometabolomics provides powerful tools for identifying global biochemical changes induced by statin treatment, providing insights about drug mechanism of action, development of side effects and basis of variation of response.

Objective

To determine whether statin-induced changes in intermediary metabolism correlated with statin-induced hyperglycemia and insulin resistance; to identify pre-drug treatment metabolites predictive of post-drug treatment increased diabetic risk.

Methods

Drug-naïve patients were treated with 40 mg/day simvastatin for 6 weeks in the Cholesterol and Pharmacogenetics (CAP) study; metabolomics by gas chromatography-time-of-flight mass-spectrometry (GC-TOF-MS) was performed on plasma pre and post treatment on 148 of the 944 participants.

Results

Six weeks of simvastatin treatment resulted in 6.9% of patients developing hyperglycemia and 25% developing changes consistent with development of pre-diabetes. Altered beta cell function was observed in 53% of patients following simvastatin therapy and insulin resistance was observed in 54% of patients. We identified initial signature of simvastatin-induced insulin resistance, including ethanolamine, hydroxylamine, hydroxycarbamate and isoleucine which, upon further replication and expansion, could be predictive biomarkers of individual susceptibility to simvastatin-induced new onset pre-type II diabetes mellitus. No patients were clinically diagnosed with T2DM.

Conclusion

Within this short 6 weeks study, some patients became hyperglycemic and/or insulin resistant. Diabetic markers were associated with decarboxylated small aminated metabolites as well as a branched chain amino acid directly linked to glucose metabolism and fatty acid biosynthesis. Pharmacometabolomics provides powerful tools for precision medicine by predicting development of drug adverse effects in sub populations of patients. Metabolic profiling prior to start of drug therapy may empower physicians with critical information when prescribing medication and determining prognosis.

Statins and risk for new-onset diabetes mellitus: A real-world cohort study using a clinical research database

Although concern regarding the increased risk for new-onset diabetes mellitus (NODM) after statin treatment has been raised, there has been a lack of evidence in real-world clinical practice, particularly in East Asians. We investigated whether statin use is associated with risk for NODM in Koreans. We conducted a retrospective cohort study using the clinical research database from electronic health records. The study cohort consisted of 8265 statin-exposed and 33,060 matched nonexposed patients between January 1996 and August 2013. Matching at a 1:4 ratio was performed using a propensity score based on age, gender, baseline glucose levels (mg/dL), and hypertension. The comparative risks for NODM with various statins (atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin) were estimated by both statin exposure versus matched nonexposed and within-class comparisons. The incidence of NODM among the statin-exposed group (6.000 per 1000 patient-years [PY]) was higher than that of the nonexposed group (3.244 per 1000 PY). The hazard ratio (HR) of NODM after statin exposure was 1.872 (95% confidence interval [CI], 1.432-2.445). Male gender (HR, 1.944; 95% CI, 1.497-2.523), baseline glucose per mg/dL (HR, 1.014; 95% CI, 1.013-1.016), hypertension (HR, 2.232; 95% CI, 1.515-3.288), and thiazide use (HR, 1.337; 95% CI, 1.081-1.655) showed an increased risk for NODM, while angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker showed a decreased risk (HR, 0.774; 95% CI, 0.668-0.897). Atorvastatin-exposed patients showed a higher risk for NODM than their matched nonexposed counterparts (HR, 1.939; 95% CI, 1.278-2.943). However, the risk for NODM was not significantly different among statins in within-class comparisons. In conclusion, an increased risk for NODM was observed among statin users in a practical healthcare setting in Korea.

Lower and higher-potency statins on glycemic control in type 2 diabetes: A retrospective cohort study

AIMS

Evidences showed a link between statins and new-onset diabetes and large clinical trials in type 2 diabetes (T2DM) suggested a mild glycemic progression in statin treated. Since this effect has not yet elucidated in real world, we investigated the effects of different statins on glycemia in T2DM clinic outpatients.

METHODS

In a retrospective cohort study, we recorded at 6 and 12months modifications of fasting glucose (FPG), HbA1c, diabetes intensification therapy and target rate for HbA1c in 421 T2DM non-users and new statin users. Statins were categorized with low or high potency.

RESULTS

Compared to statin users, no statin group showed a significant HbA1c reduction from 52.8±14.0mmol/mol to 48.2±8.5 (p=0.003) at 6months and 48.6±8.8 (p=0.007) at 12months. This trend without statins was also observed in FPG starting from 7.1±2.0mmol/l to 6.7±1.6 (p=0.12) at 6months and 6.6±1.5 (p=0.032) at 12months. Statins determined a significant diabetes treatment intensification: 48.7% vs 27.4% (p=0.002) with hazard ratio 2.4 [95% CI 1.14-5.2], p=0.022. HbA1c target was significantly lower in statin users 62.0% vs 75.4%, p=0.042. Only lower-potency statins showed a significant reduction of HbA1c from 52.0±11.1mmol/mol to 50.7±9.0 (p=0.017) and 50.7±9.5 (p=0.038) at 6 and 12months, respectively. The same effect for these statins was registered in FPG from 7.5±2.2mmol/l to 7.0±1.6 (p=0.021) at 6months and 7.2±1.5 (p=0.026) at 12months.

CONCLUSIONS

In patients receiving statin therapy a greater intensification diabetes therapy is need. This impact seems to be less pronounced by statins with lower potency.

Clinical benefits of pitavastatin: focus on patients with diabetes or at risk of developing diabetes

Despite attaining LDL-cholesterol targets, many patients with diabetes remain at risk of developing cardiovascular events. In addition, treatment with statins has been associated with a slight but significant increased risk of development of diabetes, particularly with high-intensity statins. Pitavastatin is a moderate- to high-intensity statin that effectively reduces LDL-cholesterol levels. Pitavastatin provides a sustained increase of HDL-cholesterol levels that may exhibit a neutral or positive effect on glucose metabolism, may not increase the risk of new-onset diabetes, may exhibit positive effects on renal function and urinary albumin excretion and the risk of drug–drug interactions is low. Therefore, it seems that pitavastatin should preferentially be considered in the treatment of dyslipidemia in diabetic patients or at risk of developing diabetes.

Pitavastatin improves glycated hemoglobin in patients with poorly controlled type 2 diabetes

Aims/Introduction

To investigate the effect of pitavastatin on glucose control in patients with type 2 diabetes.

Materials and Methods

Medical records of 340 patients with type 2 diabetes treated with pitavastatin or atorvastatin between 1 August 2013 and 31 May 2014 were reviewed. A total of 96 patients who had not received statins were treated with pitavastatin (N to P group). A total of 100 patients who had previously used atorvastatin were switched to pitavastatin (A to P group). A total of 144 patients continued with atorvastatin treatment. Data were collected at baseline, 3 and 6 months of treatment. Changes in glycated hemoglobin (HbA1c) level were analyzed in 222 patients who did not change their antidiabetic agent during 6 months of treatment.

Results

A negative correlation between baseline HbA1c and delta HbA1c at 6 months was found in the pitavastatin‐treated patients (N to P group: ρ = −0.329, P = 0.006; A to P group: ρ = −0.480, P < 0.001). The correlation remained similar after adjusting for age, body mass index, dose of pitavastatin, estimated glomerular filtration rate and high‐density lipoprotein cholesterol. After 6 months of treatment, the benefit of pitavastatin on HbA1c in the patients with poorly controlled diabetes was significant in both the N to P (8.1 vs 7.4%, P = 0.018) and A to P (9.7 vs 9.0%, P = 0.015) groups.

Conclusions

Pitavastatin decreases HbA1c in patients with type 2 diabetes with a higher baseline HbA1c level. The benefit on HbA1c was also observed in patients with previous use of atorvastatin.

Treatment with atorvastatin attenuates progression of insulin resistance and pancreatic fibrosis in the Otsuka Long-Evans Tokushima fatty rats

PURPOSE

The effects of statins on insulin resistance (IR) and type 2 diabetes mellitus (T2DM) are still controversial and its effects on pancreatic fibrosis are poorly defined. The purpose of this study is to examine the effects of atorvastatin on these issues using the Otsuka Long-Evans Tokushima Fatty (OLETF) rat, an animal model of IR, T2DM and pancreatic fibrosis.

METHODS

Male OLETF rats were divided into 2 groups at 6weeks of age. The first group received a standard diet until the end of experimental period at age 28weeks. The second group was given a diet containing 0.05% atorvastatin from 6weeks of age, before the onset of IR and pancreatic fibrosis. The age-matched Long-Evans Tokushima Otsuka rats without presence of IR, T2DM and pancreatic fibrosis, received a standard diet and were used as a normal control.

RESULTS

Atorvastatin slightly decreased serum fasting glucose and insulin levels, but significantly improved index of IR compared with the untreated OLETF rats. In addition, atorvastatin markedly decreased transforming growth factor-β1 mRNA expression, myeloperoxidase activity and proportion of fibrotic area, and elevated superoxide dismutase activity in the pancreas compared with the untreated OLETF rats.

CONCLUSIONS

These findings suggest that atorvastatin exerts favorable influence on progression of IR and pancreatic inflammation and fibrosis via pleiotropic effect such as anti-oxidative property.

The diabetogenic action of statins - mechanisms and clinical implications

Treatment with statins has transformed primary and secondary prevention of cardiovascular disease (CVD), including thrombotic stroke. Evidence-based data demonstrate the benefits and safety of statin therapy and help to guide clinicians in the management of populations at high risk of CVD. Nevertheless, clinical trials, meta-analyses and observational studies highlight a 10-12% increase in new-onset diabetes mellitus (NODM) among patients receiving statins. The risk further increases with intensive therapy and among individuals with known risk factors for NODM. Mechanisms underpinning this effect are not yet fully understood; however, Mendelian randomization studies suggest that they are related to lowered activity of HMG-CoA reductase, the target of statin therapy. In vitro research indicates that statins potentially impair β-cell function and decrease insulin sensitivity but how these findings relate to patients is unknown. In the clinic, statins should be prescribed on the basis of CVD risk and individual patient characteristics. In addition, diet and lifestyle interventions should be emphasized to help mitigate the risk of NODM. Individuals who develop NODM while taking statins do not exhibit increased microvascular disease, which is reassuring. In diabetes mellitus of long duration, the effect of statins on glycaemic control is small and unlikely to be clinically important.

Statins and myocardial infarction: Type, dose, and administration time: Does it matter?

Patients with ST-elevation myocardial infarction (STEMI) constitute a vulnerable group that demands the careful assessment and application of all the up-to-date clinical and experimental knowledge, with final aim, the improvement of their prognosis. Statins are an indispensable part of the primary and secondary prevention of coronary artery disease (CAD), not only due to their strong hypolipidemic effect, but also due to their numerous pleiotropic properties that play an important role in the treatment of CAD, especially when the more vulnerable group of STEMI patients is addressed. Nevertheless, there are still issues that require further discussion and clarification, such as the type of statin, the dose of the regimen, the administration time, and the treatment duration.

Nonalcoholic fatty liver disease and statins

OBJECTIVE

Nonalcoholic fatty liver disease (NAFLD) is the most frequent cause of elevated transaminase levels and affects approximately one third of the general population. Patients with NAFLD are at increased risk for cardiovascular events, which represent the leading cause of death in this population. We discuss the safety and efficacy of statins in this population.

MATERIALS/METHODS

We reviewed the most recent literature on the safety of statins in patients with NAFLD and on their effects on liver histology and cardiovascular events.

RESULTS

It appears that statins can be safely administered to patients with NAFLD, including those with elevated transaminase levels (<3 times the upper limit of normal). Post-hoc analyses of randomized controlled trials also suggest that statins might reduce cardiovascular morbidity in this population. On the other hand, there are few and controversial data on the effects of statins on liver histology in patients with NAFLD.

CONCLUSIONS

Statins appear to be safe and might also reduce cardiovascular events in patients with NAFLD. Ongoing and future studies will clarify whether statins might also have a role in the treatment of NAFLD.

Is immunity a mechanism contributing to statin-induced diabetes?

Statins lower cholesterol and are commonly prescribed for prevention and treatment of cardiovascular disease risk. Statins have pleotropic actions beyond cholesterol lowering, including decreased protein prenylation, which can alter immune function. The general anti-inflammatory effect of statins may be a key pleiotropic effect that improves cardiovascular disease risk. However, a series of findings have shown that statins increase the pro-inflammatory cytokine, IL-1β, via decreased protein prenylation in immune cells. IL-1β can be regulated by the NLRP3 inflammasome containing caspase-1. Statins have been associated with an increased risk of new onset diabetes. Inflammation can promote ineffective insulin action (insulin resistance), which often precedes diabetes. This review highlights the links between statins, insulin resistance and immunity via the NLRP3 inflammasome. We propose that statin-induced changes in immunity should be investigated as a mechanism underlying increased risk of diabetes. It is possible that statin-related insulin resistance occurs through a separate pathway from various mechanisms that confer cardiovascular benefits. Therefore, understanding the potential mechanisms that segregate statin-induced cardiovascular effects from those that cause dysglycemia may lead to improvements in this drugs class.

Risk of new-onset diabetes associated with statin use

OBJECTIVE

To identify and assess studies investigating the association between statins and new-onset diabetes and determine the clinical significance of this risk.

DATA SOURCES

A MEDLINE (1977-April 2015), Google Scholar (1997-April 2015), and International Pharmaceutical Abstracts (1977-April 2015) search was performed using the search terms hydroxymethylglutaryl-CoA reductase inhibitors, hydroxymethylglutaryl-CoA reductase inhibitors/adverse effects, statins, adverse effects, diabetes mellitus, diabetes mellitus/etiology, and drug-induced. Citations of identified articles and clinical practice guidelines were also reviewed.

STUDY SELECTION AND DATA EXTRACTION

Articles describing results from original investigations or meta-analyses specifically designed to assess the association between statins and new-onset diabetes and published in English were included.

DATA SYNTHESIS

A total of 13 cohort studies and seven meta-analyses were included. In all, 11 were retrospective cohort studies and reported some degree of increased risk of new-onset diabetes associated with statins. The two prospective cohort studies differed. One identified increased risk of new-onset diabetes, but the other did not. Increased risk was not identified when any statin was compared to placebo alone, individual statins were compared, or in the single meta-analysis that included observational studies. Overall, the meta-analyses suggest that statin therapy is associated with an increased risk of new-onset diabetes when compared to placebo or active control, and when intensive therapy is compared to moderate therapy.

CONCLUSION

Statins have been associated with a small, but statistically significant risk of new-onset diabetes. Patients with risk factors for developing diabetes mellitus may be at higher risk. This risk is likely outweighed by the benefits of reducing cardiovascular risk.

Rosuvastatin Worsens Insulin Resistance in HIV-Infected Adults on Antiretroviral Therapy

BACKGROUND

Statins are associated with increased diabetes risk in large, human immunodeficiency virus (HIV)-uninfected cohorts; the impact of statins on insulin resistance or diabetes in HIV-infected persons has not been assessed within a randomized controlled study.

METHODS

HIV-infected participants on stable antiretroviral therapy with a low-density lipoprotein cholesterol level of ≤130 mg/dL and heightened immune activation or inflammation were randomized to rosuvastatin 10 mg daily or placebo for 96 weeks. Fasting serum glucose, insulin, and hemoglobin A1C (HgbA1C) were measured; insulin resistance was estimated by calculating the homeostatic model assessment of insulin resistance (HOMA-IR); and a 2-hour oral glucose tolerance test was administered.

RESULTS

Seventy-two participants were randomized to rosuvastatin therapy and 75 to placebo. Increases in fasting glucose were observed within both groups but were not different between study arms (P = .115); changes in glucose tolerance and HgbA1C did not differ between study arms (P = .920 and P = .650, respectively). Criteria for diabetes were met by 1 participant in the rosuvastatin and 3 in the placebo arm by week 96. Compared with placebo, rosuvastatin therapy was associated with significantly greater increases in insulin and HOMA-IR (P = .008 and P = .004, respectively).

CONCLUSIONS

We detected a significant worsening in insulin resistance and an increase in the proportion of participants with impaired fasting glucose but not a clinical diagnosis of diabetes in the rosuvastatin arm. Our findings suggest that prescription of statin therapy should be accompanied by a careful consideration of the risks and benefits, particularly in patients with lower cardiovascular disease risk.

CLINICAL TRIALS REGISTRATION

NCT01218802.