BACKGROUND: Fibrates have renal toxicity limiting their use in subjects with chronic kidney disease (CKD). However, pemafibrate has fewer toxic effects on renal function. In the present analysis, we evaluated the effects of pemafibrate on the renal function of diabetic subjects with or without CKD in a real-world clinical setting.
METHODS: We performed a sub-analysis of data collected during a multi-center, prospective, observational study of the effects of pemafibrate on lipid metabolism in subjects with type 2 diabetes mellitus complicated by hypertriglyceridemia (the PARM-T2D study). The participants were allocated to add pemafibrate to their existing regimen (ADD-ON), switch from their existing fibrate to pemafibrate (SWITCH), or continue conventional therapy (CTRL). The changes in estimated glomerular filtration rate (eGFR) over 52 weeks were compared among these groups as well as among subgroups created according to CKD status.
RESULTS: Data for 520 participants (ADD-ON, n=166; SWITCH, n=96; CTRL, n=258) were analyzed. Of them, 56.7% had CKD. The eGFR increased only in the SWITCH group, and this trend was also present in the CKD subgroup (P<0.001). On the other hand, eGFR was not affected by switching in participants with severe renal dysfunction (G3b or G4) and/or macroalbuminuria. Multivariate analysis showed that being older and a switch from fenofibrate were associated with elevation in eGFR (both P<0.05).
CONCLUSIONS: A switch to pemafibrate may be associated with an elevation in eGFR, but to a lesser extent in patients with poor renal function.

Hypertriglyceridemia is the most prevalent dyslipidemia in patients with chronic kidney disease (CKD). However, research about fibrate treatment in CKD patients is limited, and assessing its benefits becomes challenging due to the frequent concurrent use of statins. Thus, this study is aimed to investigate the role of fibrate in CKD stage 3 patients with hypertriglyceridemia who did not receive other lipid-lowering agents.
This study enrolled patients newly diagnosed CKD3 with LDL-C<100mg/dL and had never received statin or other lipid-lowering agents from Chang Gung Research Database. The participants were categorized into 2 groups based on the use of fibrate: fibrate group and non-fibrate group (triglyceride >200mg/dL but not receiving fibrate treatment). The inverse probability of treatment weighting was performed to balance baseline characteristics.
Compared with the non-fibrate group (n=2020), the fibrate group (n=705) exhibited significantly lower risks of major adverse cardiac and cerebrovascular events (MACCEs) (10.4% vs. 12.8%, hazard ratios [HRs]: 0.69, 95% confidence interval [CI]: 0.50 to 0.95), AMI (2.3% vs. 3.9%, HR: 0.52, 95% CI: 0.37 to 0.73), and ischemic stroke (6.3% vs. 8.0%, HR: 0.67, 95% CI: 0.52 to 0.85). The risk of all-cause mortality (5.1% vs. 4.5%, HR: 1.09, 95% CI: 0.67 to 1.79) and death from CV (2.8% vs. 2.3%, HR: 1.07, 95% CI: 0.29 to 2.33) did not significantly differ between the 2 groups.
This study suggests that, in moderate CKD patients with hypertriglyceridemia but LDL-C < 100mg/dL who did not take other lipid-lowering agents, fibrates may be beneficial in reducing cardiovascular events.

OBJECTIVE: Previous studies have suggested that fibrates and glitazones may have a role in brain tumour prevention. We examined if there is support for these observations using primary care records from the UK Clinical Practice Research Datalink (CPRD).
METHODS: We conducted two nested case-control studies using primary and secondary brain tumours identified within CPRD between 2000 and 2016. We selected cases and controls among the population of individuals who had been treated with any anti-diabetic or anti-hyperlipidaemic medication to reduce confounding by indication.
METHODS: Adults older than 18 years registered with a general practitioner in the UK contributing data to CPRD.
RESULTS: We identified 7496 individuals with any brain tumour (4471 primary; 3025 secondary) in total. After restricting cases and controls to those prescribed any anti-diabetic or anti-hyperlipidaemic medication, there were 1950 cases and 7791 controls in the fibrate and 480 cases with 1920 controls in the glitazone analyses. Longer use of glitazones compared with all other anti-diabetic medications was associated with a reduced risk of primary (adjusted OR (aOR) 0.89 per year, 95% CI 0.80 to 0.98), secondary (aOR 0.87 per year, 95% CI 0.77 to 0.99) or combined brain tumours (aOR 0.88 per year, 95% CI 0.81 to 0.95). There was little evidence that fibrate exposure was associated with risk of either primary or secondary brain tumours.
CONCLUSIONS: Longer exposure to glitazones was associated with reduced primary and secondary brain tumour risk. Further basic science and population-based research should explore this finding in greater detail, in terms of replication and mechanistic studies.

Stroke is one of the leading causes of death worldwide. Previous studies have explored machine learning techniques for early detection of stroke patients using content-based recommendation systems. However, these models often struggle with timely detection of medications, which can be critical for patient management and decision-making regarding the prescription of new drugs. In this study, we developed a content-based recommendation model using three machine learning algorithms: Gaussian Mixture Model (GMM), Affinity Propagation (AP), and K-Nearest Neighbors (KNN), to aid Healthcare Professionals (HCP) in quickly detecting medications based on the symptoms of a patient with stroke. Our model focused on three classes of drugs: antihypertensive, anticoagulant, and fibrate. Each machine learning algorithm was used to accomplish specific tasks, thereby reducing the partial search space, computational cost, and accurately detecting a primary drug class without loss of precision and accuracy. Our proposed model, called CRGANNC (Clustering Recommendation Gaussian Affinity Nearest Neighbors Classifier), effectively addresses the sparsity and scalability issues faced by content-based recommendation models. The CRGANNC model dynamically partition clusters into sub-clusters with variable numbers based on the group, and can diagnose healthy, sick, and at-risk patients, and recommend drugs to the HCP. In addition to our analysis, we developed a semi-artificial dataset with new features such as weakness, dizziness, headache, nausea, and vomiting, using a pipeline. This dataset serves as a valuable resource for researchers in the sensitive domain of stroke, providing a starting point for building and testing models when real data is often restricted. Our work not only contributes to the development of predictive models for stroke but also establishes a framework for creating similar datasets in other sensitive domains, accelerating research efforts and improving patient care. Our experiments were conducted on our dataset consisting of 9691 patient records, with 1206 records for stroke attacks and 8485 healthy patients. The CRGANNC model achieved an average precision of 0.98, recall of 0.95 and F1-score of 0.96 across all three drugs classes. Furthermore, our model demonstrated significant improvement in computational efficiency compared to existing content-based recommendation models, reducing the processing time by 25.80% . This results indicate the effectiveness of our model in accurately detecting medications for stroke patients based on their symptoms.

Objectives Diabetic retinopathy (DR) is a major cause of blindness and its prevalence is increasing. Fibrate, specifically fenofibrate, has been shown to be efficacious in reducing the progression of DR. This study aims to determine the five-year trend of and factors associated with the prescription of fibrate among patients with DR in Perak. Methods Data on all patients with DR in 76 government health clinics in Perak who were audited between 2018 and 2022 were extracted from the National Diabetes Registry (NDR), excluding those who were lost to follow-up. Multivariable logistic regression was used to identify factors associated with the prescription of fibrates. Results Data from 4028 patients were analysed. Commonly prescribed medications were statins (n = 3466, 86.0%), metformin (n = 3212, 79.7%), and angiotensin-converting enzyme inhibitors (n = 2318, 57.5%). Only 63 (1.6%) patients were prescribed fibrate. Factors associated with the prescription of fibrates were patients from the clinics in northern (adjusted odds ratio (aOR) = 0.33, 95% CI: 0.12-0.65) and southern clusters (aOR = 0.23, 95% CI: 0.08-0.655), triglycerides > 1.7 mmol/L (aOR = 4.85, 95% CI: 1.85-12.70), and prescription of insulin (aOR = 2.77, 95% CI: 1.07-7.18) and statin (aOR = 0.10, 95% CI: 0.04-0.27). Conclusion The prescription of fibrate among patients with DR was low, highlighting a missed opportunity for early treatment and improved outcomes in primary care. The prescription of fibrates to reduce the progression of DR should be expanded to primary care. Clinicians should consider the factors associated with the non-prescription of fibrate identified when prescribing to these patients. Policies, including those at the ministry level, to enhance the availability of these medicines, including financial resources for procurement, are necessary to guarantee easy access for patients in different areas. It is crucial for healthcare providers to be knowledgeable about and follow guidelines. Moreover, improving the overall management of DR in patients with multiple comorbidities can be achieved by addressing worries about the side effects of combination therapies through educational campaigns and providing clear directives. Nevertheless, the study\'s findings should be interpreted in light of the limitations discussed.

Hypertriglyceridemia and decreased high-density lipoprotein cholesterol (HDL-C) persist despite statin therapy, contributing to residual atherosclerotic cardiovascular disease (ASCVD) risk. Asian subjects are metabolically more susceptible to hypertriglyceridemia than other ethnicities. Fenofibrate regulates hypertriglyceridemia, raises HDL-C levels, and is a recommended treatment for dyslipidemia. However, data on fenofibrate use across different Asian regions are limited. This narrative review summarizes the efficacy and safety data of fenofibrate in Asian subjects with dyslipidemia and related comorbidities (diabetes, metabolic syndrome, diabetic retinopathy, and diabetic nephropathy). Long-term fenofibrate use resulted in fewer cardiovascular (CV) events and reduced the composite of heart failure hospitalizations or CV mortality in type 2 diabetes mellitus. Fenofibrate plays a significant role in improving irisin resistance and microalbuminuria, inhibiting inflammatory responses, and reducing retinopathy incidence. Fenofibrate plus statin combination significantly reduced composite CV events risk in patients with metabolic syndrome and demonstrated decreased triglyceride and increased HDL-C levels with an acceptable safety profile in those with high CV or ASCVD risk. Nevertheless, care is necessary with fenofibrate use due to possible hepatic and renal toxicities in vulnerable individuals. Long-term trials and real-world studies are needed to confirm the clinical benefits of fenofibrate in the heterogeneous Asian population with dyslipidemia.

BACKGROUND: The high risk of major adverse cardiovascular events (MACE) in patients with chronic kidney disease (CKD) has been well described. However, the efficacy of fibrates on the risk of MACE in patients with CKD remains unclear.
METHODS: We conducted a nested case-control study using data from a large administrative database that included more than 1.5 million Japanese patients. We defined cases as CKD patients with incidences of MACE and matched them with controls based on age, sex, calendar year of cohort entry and CKD stage. Fibrate exposure timing was categorized as current, recent or past. A conditional logistic regression analysis was used to investigate the association between fibrate use and the risk of MACE.
RESULTS: Our study included 47 490 patients with CKD, with 15 830 MACE identified during a median follow-up of 9.4 months. The numbers of fibrates used during the study period were 556 (3.5%) in the case group and 1109 (3.5%) in the control group. Fibrate use was significantly associated with a decreased risk of MACE [odds ratio (OR) 0.84; 95% confidence interval (CI) 0.75-0.94], particularly for current (OR 0.81; 95% CI 0.68-0.97) and recent use (OR 0.65; 95% CI 0.48-0.90). Regarding the class effect of fibrates, pemafibrate use, but not bezafibrate or fenofibrate use, was significantly associated with a decreased risk of MACE (OR 0.73; 95% CI 0.528-0.997).
CONCLUSIONS: Recent and current fibrate use, especially pemafibrate use, was associated with a reduced risk of MACE in patients with CKD. This suggests the potential benefits of continuous fibrate therapy and the possible superiority of pemafibrate over other fibrates. However, further investigations in different populations are required to confirm the generalizability of these findings.

To assess the benefits and harms of lipid-lowering therapies used to prevent or manage cardiovascular disease including bile acid sequestrants (BAS), ezetimibe, fibrates, niacin, omega-3 supplements, proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors, and statins.
MEDLINE, the Cochrane Database of Systematic Reviews, and a grey literature search.
Systematic reviews of randomized controlled trials published between January 2017 and March 2022 looking at statins, ezetimibe, PCSK9 inhibitors, fibrates, BAS, niacin, and omega-3 supplements for preventing cardiovascular outcomes were selected. Outcomes of interest included major adverse cardiovascular events (MACE), cardiovascular mortality, all-cause mortality, and adverse events.
A total of 76 systematic reviews were included. Four randomized controlled trials were also included for BAS because no efficacy systematic review was identified. Statins significantly reduced MACE (6 systematic reviews; median risk ratio [RR]=0.74; interquartile range [IQR]=0.71 to 0.76), cardiovascular mortality (7 systematic reviews; median RR=0.85, IQR=0.83 to 0.86), and all-cause mortality (8 systematic reviews; median RR=0.91, IQR=0.88 to 0.92). Major adverse cardiovascular events were also significantly reduced by ezetimibe (3 systematic reviews; median RR=0.93, IQR=0.93 to 0.94), PCSK9 inhibitors (14 systematic reviews; median RR=0.84, IQR=0.83 to 0.87), and fibrates (2 systematic reviews; mean RR=0.86), but these interventions had no effect on cardiovascular or all-cause mortality. Fibrates had no effect on any cardiovascular outcomes when added to a statin. Omega-3 combination supplements had no effect on MACE or all-cause mortality but significantly reduced cardiovascular mortality (5 systematic reviews; median RR=0.93, IQR=0.93 to 0.94). Eicosapentaenoic acid ethyl ester alone significantly reduced MACE (1 systematic review, RR=0.78) and cardiovascular mortality (2 systematic reviews; RRs of 0.82 and 0.82). In primary cardiovascular prevention, only statins showed consistent benefits on MACE (6 systematic reviews; median RR=0.75, IQR=0.73 to 0.78), cardiovascularall-cause mortality (7 systematic reviews, median RR=0.83, IQR=0.81 to 0.90), and all-cause mortality (8 systematic reviews; median RR=0.91, IQR=0.87 to 0.91).
Statins have the most consistent evidence for the prevention of cardiovascular complications with a relative risk reduction of about 25% for MACE and 10% to 15% for mortality. The addition of ezetimibe, a PCSK9 inhibitor, or eicosapentaenoic acid ethyl ester to a statin provides additional MACE risk reduction but has no effect on all-cause mortality.

This study aims to understand the adverse drug reactions (ADRs) for non-statin antihyperlipidaemic drugs included in the China Anti-hyperlipidemic Drug Database.
An approach of Chinese national database analysis was employed to screen clinical trials involving non-statin antihyperlipidaemic drugs from 1989 to 2019.
The database was provided by the China National Medical Products Administration Information Centre.
In total, 117 clinical studies with 8800 patients were selected from 2650 clinical trials of the Anti-hyperlipidemic Drug Database.
The non-statin antihyperlipidaemic drugs were divided into three groups: (1) fibrates (fenofibrate, gemfibrozil, bezafibrate, etofylline clofibrate); (2) nicotinic acid and derivatives (niacin, acipimox) and (3) others (probucol, cholestyramine).
The results of this study show that first, gastrointestinal symptoms were the most common reactions (6.975%), which account for approximately 50% of the reported cases with ADRs. Second, cholestyramine (16.418%) and gemfibrozil (13.158%) were the most common gastrointestinal side effect-causing non-statin antihyperlipidaemic drugs, which account for one-third of the population. Third, niacin (7.879%) and gemfibrozil (5.000%) were the most likely cause of liver disease symptoms. Finally, niacin (10.909%) and acipimox (18.847%) were the major non-statin antihyperlipidaemic drugs with skin symptoms.
This study revealed that gastrointestinal symptoms were the most common ADRs of fibrates, probucol and cholestyramine in the Chinese population. For nicotinic acid and derivatives, the ADRs of skin symptoms were the most common in China.

Designing studies for lipid-metabolism-related biomarker discovery is challenging because of the high prevalence of various statin and fibrate usage for lipid-lowering therapies. When the statin and fibrate use is determined based on self-reports, patient adherence to the prescribed statin dose regimen remains unknown. A potentially more accurate way to verify a patient\'s medication adherence is by direct analytical measurements. Current analytical methods are prohibitive because of the limited panel of drugs per test and large sample volume requirement that is not available from archived samples. A 4-min-long method was developed for the detection of seven statins and three fibrates using 10 µL of plasma analyzed via reverse-phase liquid chromatography and tandem mass spectrometry. The method was applied to the analysis of 941 archived plasma samples collected from patients before cardiac catheterization. When statin use was self-reported, statins were detected in 78.6% of the samples. In the case of self-reported atorvastatin use, the agreement with detection was 90.2%. However, when no statin use was reported, 42.4% of the samples had detectable levels of statins, with a similar range of concentrations as the samples from the self-reported statin users. The method is highly applicable in population studies designed for biomarker discovery or diet and lifestyle intervention studies, where the accuracy of statin or fibrate use may strongly affect the statistical evaluation of the biomarker data.