Pharmacogenetics in cardiovascular diseases: State of the art and implementation-recommendations of the French National Network of Pharmacogenetics (RNPGx)

Empowering personalized pharmacogenomics with generative AI solutions

OBJECTIVE

This study evaluates an AI assistant developed using OpenAI's GPT-4 for interpreting pharmacogenomic (PGx) testing results, aiming to improve decision-making and knowledge sharing in clinical genetics and to enhance patient care with equitable access.

MATERIALS AND METHODS

The AI assistant employs retrieval-augmented generation (RAG), which combines retrieval and generative techniques, by harnessing a knowledge base (KB) that comprises data from the Clinical Pharmacogenetics Implementation Consortium (CPIC). It uses context-aware GPT-4 to generate tailored responses to user queries from this KB, further refined through prompt engineering and guardrails.

RESULTS

Evaluated against a specialized PGx question catalog, the AI assistant showed high efficacy in addressing user queries. Compared with OpenAI's ChatGPT 3.5, it demonstrated better performance, especially in provider-specific queries requiring specialized data and citations. Key areas for improvement include enhancing accuracy, relevancy, and representative language in responses.

DISCUSSION

The integration of context-aware GPT-4 with RAG significantly enhanced the AI assistant's utility. RAG's ability to incorporate domain-specific CPIC data, including recent literature, proved beneficial. Challenges persist, such as the need for specialized genetic/PGx models to improve accuracy and relevancy and addressing ethical, regulatory, and safety concerns.

CONCLUSION

This study underscores generative AI's potential for transforming healthcare provider support and patient accessibility to complex pharmacogenomic information. While careful implementation of large language models like GPT-4 is necessary, it is clear that they can substantially improve understanding of pharmacogenomic data. With further development, these tools could augment healthcare expertise, provider productivity, and the delivery of equitable, patient-centered healthcare services.

Genetic Determinants of Response to Statins in Cardiovascular Diseases

Despite extensive efforts to identify patients with cardiovascular disease (CVD) who could most benefit from the treatment approach, patients vary in their benefit from therapy and propensity for adverse drug events. Genetic variability in individual responses to drugs (pharmacogenetics) is considered an essential determinant in responding to a drug. Thus, understanding these pharmacogenomic relationships has led to a substantial focus on mechanisms of disease and drug response. In turn, understanding the genomic and molecular bases of variables that might be involved in drug response is the main step in personalized medicine. There is a growing body of data evaluating drug-gene interactions in recent years, some of which have led to FDA recommendations and detection of markers to predict drug responses (e.g., genetic variant in VKORC1 and CYP2C9 genes for prediction of drug response in warfarin treatment). Also, statins are widely prescribed drugs for the prevention of CVD. Atorvastatin, fluvastatin, rosuvastatin, simvastatin, and lovastatin are the most common statins used to manage dyslipidemia. This review provides an overview of the current knowledge on the pharmacogenetics of statins, which are being used to treat cardiovascular diseases.

PAnno: A pharmacogenomics annotation tool for clinical genomic testing

Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno. Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.

A Robust and Fast/Multiplex Pharmacogenetics Assay to Simultaneously Analyze 17 Clinically Relevant Genetic Polymorphisms in CYP3A4, CYP3A5, CYP1A2, CYP2C9, CYP2C19, CYP2D6, ABCB1, and VKORC1 Genes

In the field of pharmacogenetics, the trend is to analyze a panel of several actionable genetic polymorphisms. It may require the use of high-throughput sequencing which demands expensive reagents/instruments and specific skills to interpret results. As an alternative, the aim of this work was to validate an easy, fast, and inexpensive multiplex pharmacogenetics assay to simultaneously genotype a panel of 17 clinically actionable variants involved in drug pharmacokinetics/pharmacodynamics. We designed primers to perform a multiplex PCR assay using a single mix. Primers were labeled by two fluorescent dye markers to discriminate alleles, while the size of the PCR fragments analyzed by electrophoresis allowed identifying amplicon. Polymorphisms of interest were CYP3A4*22, CYP3A5*3, CYP1A2*1F, CYP2C9*2-*3, CYP2C19*2-*3-*17, VKORC1-1639G > A, ABCB1 rs1045642-rs1128503-rs2229109-rs2032582, and CYP2D6*3-*4-*6-*9. The assay was repeatable and a minimum quantity of 10 ng of DNA/ sample was needed to obtain accurate results. The method was applied to a validation cohort of 121 samples and genotyping results were consistent with those obtained with reference methods. The assay was fast and cost-effective with results being available within one working-day. This robust assay can easily be implemented in laboratories as an alternative to cumbersome simplex assays or expensive multiplex approaches. Together it should widespread access to pharmacogenetics in clinical routine practice.

Combining familial hypercholesterolemia and statin genetic studies as a strategy for the implementation of pharmacogenomics. A multidisciplinary approach

The diagnostic process of familial hypercholesterolemia frequently involves the use of genetic studies. Patients are treated with lipid-lowering drugs, frequently statins. Although pharmacogenomic clinical practice guidelines focusing on genotype-based statin prescription have been published, their use in routine clinical practice remains very modest.We have implemented a new NGS strategy that combines a panel of genes related to familial hypercholesterolemia with genomic regions related to the pharmacogenomics of lipid-lowering drugs described in clinical practice guidelines and in EMA and FDA drug labels. A multidisciplinary team of doctors, biologists, and pharmacists creates a clinical report that provides diagnostic and therapeutic findings using a knowledge management and clinical decision support system, as well as an algorithm for treatment selection.For 12 months, a total of 483 genetic diagnostic studies for familial hypercholesterolemia were carried out, of which 221 (45.8%) requested a complementary pharmacogenomic test. Of these 221 patients, 66.5% were carriers of actionable variants in any of the studied pharmacogenomic pathways: 46.6% of patients in one pathway, 19.0% in two pathways, and 0.9% in three pathways. 45.7% of patients could have a response to atorvastatin different from that of the reference population, 45.7% for simvastatin and lovastatin, 29.0% for fluvastatin, and 6.7% patients for pitavastatin.This implementation approach facilitates the incorporation of pharmacogenomic studies in clinical care practice, it does not add complexity nor additional steps to laboratory processes, and improves the pharmacotherapeutic process of patients.

Ethnic Diversity and Warfarin Pharmacogenomics

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

The effects of HMG-CoA reductase inhibitors on disease activity in multiple sclerosis: A systematic review and meta-analysis

OBJECTIVE

To assess whether statins (3‑hydroxy-3-methylglutaryl coenzyme A reductase inhibitors) exert disease-modifying effects in multiple sclerosis (MS).

APPROACH

A systematic review and meta-analysis was performed including randomized-controlled clinical trials (RCTs) on statin use in MS. A random-effects model was applied to calculate pooled estimates and odds ratios (ORs) with corresponding 95% confidence intervals (CIs), when comparing patients treated with statins alone or adjunct to disease modifying treatment (DMT) to non-statin-treated patients.

RESULTS

We identified 7 RCTs including 789 patients with relapsing-remitting MS (RRMS), all of whom received additional DMT with IFN-β. Single identified RCTs in secondary-progressive MS (SPMS), clinically isolated syndrome (CIS) and optic neuritis (ON) were not meta-analyzed. In RRMS, add-on statin use was not associated with the risk of clinical relapse (OR=1.30, 95%CI: 0.901.87) or EDSS-progression from baseline, neither appeared related to the risk of new contrast-enhancing or T2 lesions (OR=1.28, 95%CI: 0.364.58), and the risk of whole-brain volume reduction on MRI. Add-on statins to IFN-β were safe and well-tolerated. In SPMS, stand-alone simvastatin led to significantly reduced annualized rate of whole-brain volume reduction. In CIS and ON, statins were associated with reduced risk for new T2 lesions and improved visual recovery, respectively.

CONCLUSIONS

We detected no benefit from statin treatment as add-on to IFN-β in RRMS. However, a potential beneficial effect in SPMS, CIS and ON deserves independent confirmation and further evaluation within adequately powered RCTs.

Pharmacogenetics to Avoid Adverse Reactions in Cardiology: Ready for Implementation?

Cardiovascular Diseases (CVs) are one of the main causes of mortality and disability around the world. Advances in drug treatment have greatly improved survival and quality of life in the past decades, but associated adverse events remain a relevant problem. Pharmacogenetics can help individualize cardiovascular treatment, reducing associated toxicities and improving outcomes. Several scientific societies and working groups periodically review available studies and provide consensus recommendations for those gene-drug pairs with a sufficient level of evidence. However, these recommendations are rarely mandatory, and the indications on how to adjust treatment can vary between different guidelines, which limits their clinical applicability. The aim of this review is to compile, compare and discuss available guidelines and recommendations by the main Pharmacogenetics Consortiums (Clinical Pharmacogenetics Implementation Consortium (CPIC); Dutch Pharmacogenetics Working Group (DPWG); the French Network of Pharmacogenetics (Réseau national de pharmacogénétique (RNPGx) and The Canadian Pharmacogenomics Network for Drug Safety (CPNDS) regarding how to apply pharmacogenetic results to optimize pharmacotherapy in cardiology. Pharmacogenetic recommendations included in European or American drug labels, as well as those included in the European Society of Cardiology (ESC) and the American College of Cardiology (ACC) and the American Heart Association (AHA) treatment guidelines are also discussed.

A Cost-Consequence Analysis of Preemptive SLCO1B1 Testing for Statin Myopathy Risk Compared to Usual Care

There is a well-validated association between SLCO1B1 (rs4149056) and statin-associated muscle symptoms (SAMS). Preemptive SLCO1B1 pharmacogenetic (PGx) testing may diminish the incidence of SAMS by identifying individuals with increased genetic risk before statin initiation. Despite its potential clinical application, the cost implications of SLCO1B1 testing are largely unknown. We conducted a cost-consequence analysis of preemptive SLCO1B1 testing (PGx+) versus usual care (PGx-) among Veteran patients enrolled in the Integrating Pharmacogenetics in Clinical Care (I-PICC) Study. The assessment was conducted using a health system perspective and 12-month time horizon. Incremental costs of SLCO1B1 testing and downstream medical care were estimated using data from the U.S. Department of Veterans Affairs' Managerial Cost Accounting System. A decision analytic model was also developed to model 1-month cost and SAMS-related outcomes in a hypothetical cohort of 10,000 Veteran patients, where all patients were initiated on simvastatin. Over 12 months, 13.5% of PGx+ (26/193) and 11.2% of PGx- (24/215) participants in the I-PICC Study were prescribed Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline-concordant statins (Δ2.9%, 95% CI -4.0% to 10.0%). Differences in mean per-patient costs for lipid therapy prescriptions, including statins, for PGx+ compared to PGx- participants were not statistically significant (Δ USD 9.53, 95% CI -0.86 to 22.80 USD). Differences in per-patient costs attributable to the intervention, including PGx testing, lipid-lowering prescriptions, SAMS, laboratory and imaging expenses, and primary care and cardiology services, were also non-significant (Δ- USD 1004, 95% CI -2684 to 1009 USD). In the hypothetical cohort, SLCO1B1-informed statin therapy averted 109 myalgias and 3 myopathies at 1-month follow up. Fewer statin discontinuations (78 vs. 109) were also observed, but the SLCO1B1 testing strategy was 96 USD more costly per patient compared to no testing (124 vs. 28 USD). The implementation of SLCO1B1 testing resulted in small, non-significant increases in the proportion of patients receiving CPIC-concordant statin prescriptions within a real-world primary care context, diminished the incidence of SAMS, and reduced statin discontinuations in a hypothetical cohort of 10,000 patients. Despite these effects, SLCO1B1 testing administered as a standalone test did not result in lower per-patient health care costs at 1 month or over 1 year of treatment. The inclusion of SLCO1B1, among other well-validated pharmacogenes, into preemptive panel-based testing strategies may provide a better balance of clinical benefit and cost.

Pharmacogenetics to guide cardiovascular drug therapy

Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.

Application of Ultrasound Virtual Reality in the Diagnosis and Treatment of Cardiovascular Diseases

Cardiovascular disease is a common chronic disease in the medical field, which has a great impact on the health of Chinese residents (especially the elderly). At present, the effectiveness of the prevention and treatment of cardiovascular diseases in my country is not optimistic. Overall, the prevalence and mortality of CVD are still on the rise. The timely and effective detection and treatment of cardiovascular and cerebrovascular diseases are of great practical significance to improve the health of residents and to carry out prevention and treatment. This article aims to study the application of ultrasound-based virtual reality technology in the diagnosis and treatment of cardiovascular diseases to improve the efficiency and accuracy of the diagnosis of cardiovascular and cerebrovascular diseases by medical staff. The focus is on the application of feature attribute selection related algorithms and classification related algorithms in medical and health diagnosis systems, and a cardiovascular and cerebrovascular disease diagnosis system based on naive Bayes algorithm and improved genetic algorithm is designed and developed. The system builds a diagnostic model for cardiovascular and cerebrovascular diseases and diagnoses and displays the corresponding results based on the patient's examination data. This paper first puts forward the theoretical concepts of ultrasonic virtual reality technology, scientific computing visualization, genetic algorithm, naive Bayes algorithm, and surgery simulation system and describes them in detail. Then, we construct a three-dimensional ultrasonic virtual measurement system, from the collection and reconstruction of image data to the filtering and segmentation of image data, plus the application of three-dimensional visualization and virtual reality technology to construct a three-dimensional measurement system. The experimental results in this paper show that 10 isolated congenital heart disease models with atrial septal defect (ASD) established through the use of three-dimensional visualization and virtual reality technology measured the short diameter, long diameter, and area of the atrial septal defect in the left and right atria. Finally, a value of L less than 0.05 indicates that the statistics are meaningful, and a value of r generally greater than 0.9 indicates that the virtual measurement result is highly correlated with the real measurement result.

Applications for pharmacogenomics in pharmacy practice: A scoping review

BACKGROUND

Pharmacogenomics (PGx) can provide valuable pharmacokinetic and pharmacodynamic information for the pharmacist's assessment of drug therapy, especially within medication therapy management (MTM) services. However, no review has comprehensively mapped the pharmacists' use of PGx in practice-based research. Doing so would allow future researchers, practitioners, and policy-makers to identify the ideal populations and settings for PGx implementation within the pharmacy.

OBJECTIVE

The purpose of this review is to identify the evidence to date of PGx use in pharmacy practice.

METHODS

A scoping review was conducted to find all studied non-oncologic pharmacy practices incorporating PGx testing. Search terms were applied to 5 databases and relevant journals. Characteristics of patients, pharmacy settings, genetic tests, and outcomes were summarized to determine models most likely to benefit patients.

RESULTS

The search identified 43 studies on the use of PGx by pharmacists published between 2007 and 2020. CYP2C19 testing with antiplatelets was the most studied model, found in both community and institutional settings. It also was the most actionable test: approximately 30% of patients have polymorphisms indicating a need for alternative antiplatelets, and identifying these patients can reduce morbidity and mortality by more than 50%. As technology shifts, broader studies using multi-gene panel tests within MTM demonstrate an approximate 50% decrease in emergency visits and hospitalizations in elderly polypharmacy patients. Clinical benefit or drug-gene interactions are also found in other cardiovascular, psychiatric, analgesic, and gastrointestinal indications. No evaluations of actual costs or of pharmacist prescribing within pharmacy-based PGx have been performed. Facilitators towards successful PGx implementation included pharmacist education, collaboration with other healthcare providers, and the use of clinical decision software.

CONCLUSIONS

Pharmacogenomic testing has demonstrated feasibility and improved medication outcomes in pharmacy practice, including in the community pharmacy. Further PGx research should be directed towards pharmacist prescribing, pharmacist education, and pharmacoeconomics.

Use of Clopidogrel and Proton Pump Inhibitors Alone or in Combinations in Persons with Diabetes in Denmark; Potential for CYP2C19 Genotype-Guided Drug Therapy

Background: Clopidogrel and proton pump inhibitors (PPIs) are among the most used drugs in Denmark for which there exists pharmacogenomics (PGx)-based dosing guidelines and FDA annotations. In this study, we further scrutinized the use of clopidogrel and PPIs when prescriptions were redeemed from Danish Pharmacies alone or in combination in the Danish population and among persons with diabetes in Denmark. The focus deals with the potential of applying PGx-guided antiplatelet therapy taking both drug–drug interactions (DDI) and drug–gene interactions (DGI) into account. Methods: The Danish Register of Medicinal Product Statistics was the source to retrieve consumption data. Results: The consumption of PPIs and clopidogrel in terms of prevalence (users/1000 inhabitants) increased over a five-year period by 6.3% to 103.1 (PPIs) and by 41.7% to 22.1 (clopidogrel), respectively. The prevalence of the use of clopidogrel and PPIs in persons with diabetes are 3.8 and 2.1–2.8 times higher compared to the general population. When redeemed in combination, the prevalence increased to 4.7. The most used combination was clopidogrel and pantoprazole. Conclusions: The use of clopidogrel and PPIs either alone or in combination is quite widespread, in particular among the elderly and persons with diabetes. This further supports the emerging need of accessing and accounting for not only DDI but also for applying PGx-guided drug therapy in clinical decision making for antiplatelet therapy with clopidogrel having a particular focus on persons with diabetes and the elderly.

Anatomical distribution and expression of CYP in humans: Neuropharmacological implications

The cytochrome P450 (CYP450) superfamily is responsible for the metabolism of most xenobiotics and pharmacological treatments generally used in clinical settings. Genetic factors as well as environmental determinants acting through fine epigenetic mechanisms modulate the expression of CYP over the lifespan (fetal vs. infancy vs. adult phases) and in diverse organs. In addition, pathological processes might alter the expression of CYP. In this selective review, we sought to summarize the evidence on the expression of CYP focusing on three specific aspects: (a) the anatomical distribution of the expression in body districts relevant in terms of drug pharmacokinetics (liver, gut, and kidney) and pharmacodynamics, focusing for the latter on the brain, since this is the target organ of psychopharmacological agents; (b) the patterns of expression during developmental phases; and (c) the expression of CYP450 enzymes during pathological processes such as cancer. We showed that CYP isoforms show distinct patterns of expression depending on the body district and the specific developmental phases. Of particular relevance for neuropsychopharmacology is the complex regulatory mechanisms that significantly modulate the complexity of the pharmacokinetic regulation, including the concentration of specific CYP isoforms in distinct areas of the brain, where they could greatly affect local substrate and metabolite concentrations of drugs.

Pharmacogenetics Guidelines: Overview and Comparison of the DPWG, CPIC, CPNDS, and RNPGx Guidelines

Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

Pharmacogenomics guidelines: Current status and future development

Genetic polymorphisms impact biological responses to drugs. Current pharmacogenomics guidelines formulated by different countries, such as the Clinical Pharmacogenetics Implementation Consortium, the Dutch Pharmacogenetics Working Group, the Canadian Pharmacogenomics Network for Drug Safety, and the French National Network (Réseau) of Pharmacogenetics, play important roles in clinical practices. However, the standards for these guidelines vary significantly, resulting in differences in recommendations. The present article discusses these differences by head-to-head comparison of the existing pharmacogenomics guidelines and proposes new strategies for their future development.

Pharmacoepidemiology of statins

The evaluation of the real-life benefits and risks of statins in population is a major pharmacoepidemiological issue, given their widespread use for cardiovascular prevention. The purpose of this review was not to be exhaustive but to show the contributions of pharmacoepidemiology for various aspects of the evaluation of statins such as real-life drug use, effectiveness and risk. Statins are among the most used drugs in the world, but recent data show a slight decrease in use. Actual statin users are older, and have more comorbidities than those studied in clinical trials, but this does not seem to compromise their effectiveness, unlike the compliance issues that are common with these drugs. Beyond the known adverse reactions of statins from the clinical trials, risks of statins can be varied and sometimes difficult to evaluate, considering the ubiquity of cholesterol throughout the body, from drug or endogenous molecule metabolism to the construction of cell membranes or cell activities.

Impact of SLCO1B1 Pharmacogenetic Testing on Patient and Healthcare Outcomes: A Systematic Review

Demonstrated improvements in patient outcomes will facilitate the clinical implementation of pharmacogenetic testing. Using the association between solute carrier organic anion transporter family member 1B1 (SLCO1B1) and statin-associated muscle symptoms (SAMSs) as a model, we conducted a systematic review of patient outcomes after delivery of SLCO1B1 results. Using PubMed and Embase searches through December 19, 2017, we identified 37 eligible records reporting preliminary or final outcomes, including six studies delivering only SLCO1B1 results and five large healthcare system-based implementation projects of multipharmacogene panels. Two small trials have demonstrated at least short-term improvements in low-density lipoprotein cholesterol after SLCO1B1 testing among previously statin intolerant patients. Evidence from large implementation projects suggests that SLCO1B1 results may change prescribing patterns for some high-risk patients. No study has reported improvements in SAMSs or cardiovascular events or tracked the economic outcomes of SLCO1B1 testing. Ongoing studies should collect and report outcomes relevant to pharmacogenetics stakeholders.