Patterns of serum laboratory monitoring for safety and efficacy in patients on chronic statin therapy

Assessment of prescription pattern and impact of statin in lipid profile among ischemic heart disease patients

BACKGROUND

Analysis of prescription patterns and lipid profiles can play a crucial role in rational drug use and patient safety. This study aimed to analyze the prescription pattern and impact of statin in lipid profile among ischemic heart disease (IHD) patients.

MATERIALS AND METHODS

A prospective observational study was conducted for 7 months in the cardiology department. IHD patients above 18 years and undergoing statin therapy for at least 3 months were enrolled. Patients with elevated liver enzymes and unfit for statin therapy, pregnant women, psychiatry patients, and critically ill subjects were excluded.

RESULTS

Of the total participants, 214 (71.8%) were males and 84 (28.2%) were females, with a mean age of 62.55 ± 9.56 years. The most common age group diagnosed with IHD was between 60 and 69 years. Hypertension was observed in 64.4% of the patients, while diabetes was present in 55.7% as the most commonly associated comorbidities. The majority of patients (75.8%) received atorvastatin. The prescription pattern for various drug classes included proton pump inhibitors (93%), antiplatelet agents (82.2%), statins (82.2%), nitrates (60.4%), beta-blockers (34.6%), diuretics (16.8%), biguanides (17.4%), and insulin (15.1%). After 3 months of statin therapy, a statistically significant change was observed in the lipid profile (P < 0.001).

CONCLUSION

Statin agents were the most frequently prescribed class of drugs, followed by antiplatelets. Significant improvements were observed in the lipid profile after a 3-month course of statin therapy. Effective therapeutic monitoring can significantly impact a positive health outcome in patients.

Enzalutamide: Understanding and Managing Drug Interactions to Improve Patient Safety and Drug Efficacy

Enzalutamide is an oral androgen receptor signaling inhibitor utilized in the treatment of men with prostate cancer. It is a moderate inducer of the cytochrome P450 (CYP) enzymes CYP2C9 and CYP2C19, and a strong inducer of CYP3A4. It was also shown to be a mild inhibitor of the efflux transporter P-glycoprotein in patients with prostate cancer. Enzalutamide is primarily metabolized by CYP3A4 and CYP2C8. The risk of enzalutamide drug interactions arises primarily when it is coadministered with other drugs that interact with these CYPs, including CYP3A4. In this review, we begin by providing an overview of enzalutamide including its dosing, use in special populations, pharmacokinetics, changes to its prescribing information, and potential for interaction with coadministered drugs. Enzalutamide interactions with drugs from a wide range of medication classes commonly prescribed to patients with prostate cancer are described, including oral androgen deprivation therapy, agents used to treat a range of cardiovascular diseases, antidiabetic drugs, antidepressants, anti-seizure medications, common urology medications, analgesics, proton pump inhibitors, immunosuppressants, and antigout drugs. Enzalutamide interactions with common vitamins and supplements are also briefly discussed. This review provides a resource for healthcare practitioners and patients that will help provide a basis for the understanding and management of enzalutamide drug-drug interactions to inform decision making, improve patient safety, and optimize drug efficacy.

Molecular targets of statins and their potential side effects: Not all the glitter is gold

Statins are a class of drugs widely used worldwide to manage hypercholesterolemia and the prevention of secondary heart attacks. Currently, available statins vary in terms of their pharmacokinetic and pharmacodynamic profiles. Although the primary target of statins is the inhibition of HMG-CoA reductase (HMGR), the rate-limiting enzyme in cholesterol biosynthesis, statins exhibit many pleiotropic effects downstream of the mevalonate pathway. These pleiotropic effects include the ability to reduce myocardial fibrosis, pathologic cardiac disease states, hypertension, promote bone differentiation, anti-inflammatory, and antitumor effects through multiple mechanisms. Although these pleiotropic effects of statins may be a cause for enthusiasm, there are many adverse effects that, for the most part, are unappreciated and need to be highlighted. These adverse effects include myopathy, new-onset type 2 diabetes, renal and hepatic dysfunction. Although these adverse effects may be relatively uncommon, considering the number of people worldwide who use statins daily, the actual number of people affected becomes quite large. Also, co-administration of statins with several other medications, herbal agents, and foods, which interact through common enzymatic pathways, can have untoward clinical consequences. In this review, we address these concerns.

Cost-effectiveness of cascade genetic testing for familial hypercholesterolemia in the United States: A simulation analysis

Objective There is no coordinated cascade testing program for familial hypercholesterolemia (FH) in the U.S. We evaluated the contemporary cost-effectiveness of cascade genetic testing relatives of FH probands with a pathogenic variant.

Methods

A simulation model was created to simulate multiple family trees starting with progenitor individuals carrying a pathogenic variant for FH who were followed through several generations. This approach allowed us to examine a family tree that had grown sufficiently to have large numbers of relatives across multiple degrees of relatedness. The model estimated costs and life years gained (LYG) when cascade genetic testing was implemented for relatives of FH probands identified through standard care who were at or older than designated age thresholds (5, 10, 15, 20, 25, 30, 35, 40). Costs were valued in 2018 U.S. dollars. Future costs and LYG projected by the model were discounted at an annual rate of 3%.

Results

For 1st degree relatives, cascade testing at every age threshold resulted in a positive number of average LYG per person, though this number decreased as testing was started at higher age thresholds. Testing was not cost-effective if initiated at an age threshold of 40 and older but was cost-effective at younger age thresholds, with a discounted cost per LYG per person of less than $50,000. For 2nd degree relatives, testing was cost-effective with a screening age threshold of 10 but no longer cost-effective at a threshold of 15 or higher. In more distant relatives, cascade genetic testing was not beneficial or cost-effective.

Conclusions

Based on our simulation model, cascade genetic testing for FH in the U.S. is cost-effective if started before age 40 in 1st degree relatives and before age 15 in 2nd degree relatives.

Reducing liver function tests for statin monitoring: an observational comparison of two clinical commissioning groups

BACKGROUND

Current liver function testing for statin monitoring is largely unnecessary and costly. Statins do not cause liver disease. Both reduction in test frequency and use of a single alanine transaminase (ALT) rather than a full seven analyte liver function test (LFT) array would reduce cost and may benefit patients.

AIM

To assess LFT testing in relation to statin use and evaluate an intervention to reduce full-array LFTs ordered by GPs for statin monitoring.

DESIGN AND SETTING

Two-year cross-sectional time series in two east London clinical commissioning groups (CCGs) with 650 000 patients. One CCG received the intervention; the other did not.

METHOD

The intervention comprised local guidance on LFTs for statin monitoring and access to a single ALT rather than full LFT array.

RESULTS

Of the total population, 17.6% were on statins, accounting for 43.2% of total LFTs. In the population without liver disease, liver function tests were 3.6 times higher for those on statins compared with those who were not. Following intervention there was a significant reduction in the full LFT array per 1000 people on statins, from 70.3 (95% confidence interval [CI] = 66.3 to 74.6) in the pre-intervention year, to 58.1 (95% CI = 55.5 to 60.7) in the post-intervention year (P<0.001). In the final month, March 2016, the rate was 53.2, a 24.3% reduction on the pre-intervention rate.

CONCLUSION

This simple and generalisable intervention, enabling ordering of a single ALT combined with information recommending prudent rather than periodic testing, reduced full LFT testing by 24.3% in people on statins. This is likely to have patient benefit at reduced cost.