Pharmacogenetics and healthcare outcomes in patients with chronic heart failure

An Analysis of Pharmacogenomic-Guided Pathways and Their Effect on Medication Changes and Hospital Admissions: A Systematic Review and Meta-Analysis

Ninety-five percent of the population are estimated to carry at least one genetic variant that is discordant with at least one medication. Pharmacogenomic (PGx) testing has the potential to identify patients with genetic variants that puts them at risk of adverse drug reactions and sub-optimal therapy. Predicting a patient's response to medications could support the safe management of medications and reduce hospitalization. These benefits can only be realized if prescribing clinicians make the medication changes prompted by PGx test results. This review examines the current evidence on the impact PGx testing has on hospital admissions and whether it prompts medication changes. A systematic search was performed in three databases (Medline, CINAHL and EMBASE) to search all the relevant studies published up to the year 2020, comparing hospitalization rates and medication changes amongst PGx tested patients with patients receiving treatment-as-usual (TAU). Data extracted from full texts were narratively synthesized using a process model developed from the included studies, to derive themes associated to a suggested workflow for PGx-guided care and its expected benefit for medications optimization and hospitalization. A meta-analysis was undertaken on all the studies that report the number of PGx tested patients that had medication change(s) and the number of PGx tested patients that were hospitalized, compared to participants that received TAU. The search strategy identified 5 hospitalization themed studies and 5 medication change themed studies for analysis. The meta-analysis showed that medication changes occurred significantly more frequently in the PGx tested arm across 4 of 5 studies. Meta-analysis showed that all-cause hospitalization occurred significantly less frequently in the PGx tested arm than the TAU. The results show proof of concept for the use of PGx in prescribing that produces patient benefit. However, the review also highlights the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems; namely patient involvement in PGx prescribing decisions, thus a better understanding of the perspective of patients and prescribers. We highlight the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems.

Pharmacogenomics in Older Adults: An Integrative Review

Through pharmacogenomics testing, identifying genetic variants that influence how individuals respond to medications could potentially decrease the "trial and error" approach to prescribing medications, maximize beneficial effects, and reduce risks of adverse drug events. Yet, pharmacogenomics testing is still subject to an ongoing debate over its clinical validity and utility. The purpose of the current integrative review was to examine and synthesize evidence on the clinical application of pharmacogenomics in medication management among older adults. Gaps were found, such as lack of studies investigating the prospective use of pharmacogenomics testing to improve clinical outcomes and lack of strong evidence on the clinical validity and utility of pharmacogenomics testing in the medication management of older adults. However, the review identified evidence for the potential benefits of pharmacogenomics testing to improve older adults' clinical outcomes that warrant further investigation. [Research in Gerontological Nursing, 14(4), 211-220.].

Examination of Metoprolol Pharmacokinetics and Pharmacodynamics Across CYP2D6 Genotype-Derived Activity Scores

Recent CYP2D6 phenotype standardization efforts by CYP2D6 activity score (AS) are based on limited pharmacokinetic (PK) and pharmacodynamic (PD) data. Using data from two independent clinical trials of metoprolol, we compared metoprolol PK and PD across CYP2D6 AS with the goal of determining whether the PK and PD data support the new phenotype classification. S‐metoprolol apparent oral clearance (CLo), adjusted for clinical factors, was correlated with CYP2D6 AS (P < 0.001). The natural log of CLo was lower with an AS of 1 (7.6 ± 0.4 mL/minute) vs. 2–2.25 (8.3 ± 0.6 mL/minute; P = 0.012), similar between an AS of 1 and 1.25–1.5 (7.8 ± 0.5 mL/minute; P = 0.702), and lower with an AS of 1.25–1.5 vs. 2–2.25 (P = 0.03). There was also a greater reduction in heart rate with metoprolol among study participants with AS of 1 (−10.8 ± 5.5) vs. 2–2.25 (−7.1 ± 5.6; P < 0.001) and no significant difference between those with an AS of 1 and 1.25–1.5 (−9.2 ± 4.7; P = 0.095). These data highlight linear trends among CYP2D6 AS and metoprolol PK and PD, but inconsistencies with the phenotypes assigned by AS based on the current standards. Overall, this case study with metoprolol suggests that utilizing CYP2D6 AS, instead of collapsing AS into phenotype categories, may be the most precise approach for utilizing CYP2D6 pharmacogenomics in clinical practice.

Pharmacogenetic factors affecting β-blocker metabolism and response

INTRODUCTION

β-blockers are among the most widely prescribed of all drugs, used for treatment of a large number of cardiovascular diseases. Herein we evaluate literature pertaining to pharmacogenetics of β-blocker therapy, provide insight into the robustness of the genetic associations, and determine the appropriateness for translating these genetic associations into clinical practice.

AREAS COVERED

A literature search was conducted using PubMed to collate evidence on associations between CYP2D6, ADRB1, ADRB2, and GRK5 genetic variation and drug-response outcomes in the presence of β-blocker exposure. Pharmacokinetic, pharmacodynamic, and clinical outcomes studies were included if genotype data and β-blocker exposure were documented.

EXPERT OPINION

Substantial data suggest that specific ADRB1 and GRK5 genotypes are associated with improved β-blocker efficacy and have potential for use to guide therapy decisions in the clinical setting. While the data do not justify ordering a CYP2D6 pharmacogenetic test, if CYP2D6 genotype is available in the electronic health record, there may be clinical utility for understanding dosing of β-blockers.

Practical Pharmacogenomic Approaches to Heart Failure Therapeutics

OPINION STATEMENT

The major challenge in applying pharmacogenomics to everyday clinical practice in heart failure (HF) is based on (1) a lack of robust clinical evidence for the differential utilization of neurohormonal antagonists in the management of HF in different subgroups, (2) inconsistent results regarding appropriate subgroups that may potentially benefit from an alternative strategy based on pharmacogenomic analyses, and (3) a lack of clinical trials that focused on testing gene-guided treatment in HF. To date, all pharmacogenomic analyses in HF have been conducted as post hoc retrospective analyses of clinical trial data or of observational patient series studies. This is in direct contrast with the guideline-directed HF therapies that have demonstrated their safety and efficacy in the absence of pharmacogenomic guidance. Therefore, the future of clinical applications of pharmacogenomic testing will largely depend on our ability to incorporate gene-drug interactions into the prescribing process, requiring that preemptive and cost-effective testing be paired with decision-support tools in a value-based care approach.

Utilizing an integrated infrastructure for outcomes research: a systematic review

OBJECTIVE

To explore the ability of an integrated health information infrastructure to support outcomes research.

METHODS

A systematic review of articles published from 1983 to 2012 by Regenstrief Institute investigators using data from an integrated electronic health record infrastructure involving multiple provider organisations was performed. Articles were independently assessed and classified by study design, disease and other metadata including bibliometrics.

RESULTS

A total of 190 articles were identified. Diseases included cognitive, (16) cardiovascular, (16) infectious, (15) chronic illness (14) and cancer (12). Publications grew steadily (26 in the first decade vs. 100 in the last) as did the number of investigators (from 15 in 1983 to 62 in 2012). The proportion of articles involving non-Regenstrief authors also expanded from 54% in the first decade to 72% in the last decade. During this period, the infrastructure grew from a single health system into a health information exchange network covering more than 6 million patients. Analysis of journal and article metrics reveals high impact for clinical trials and comparative effectiveness research studies that utilised data available in the integrated infrastructure.

DISCUSSION

Integrated information infrastructures support growth in high quality observational studies and diverse collaboration consistent with the goals for the learning health system. More recent publications demonstrate growing external collaborations facilitated by greater access to the infrastructure and improved opportunities to study broader disease and health outcomes.

CONCLUSIONS

Integrated information infrastructures can stimulate learning from electronic data captured during routine clinical care but require time and collaboration to reach full potential.

Pharmacogenomics in heart failure: where are we now and how can we reach clinical application?

Heart failure is becoming increasingly prevalent in the United States and is a significant cause of morbidity and mortality. Several therapies are currently available to treat this chronic illness; however, clinical response to these treatment options exhibit significant interpatient variation. It is now clearly understood that genetics is a key contributor to diversity in therapeutic response, and evidence that genetic polymorphisms alter the pharmacokinetics, pharmacodynamics, and clinical response of heart failure drugs continues to accumulate. This suggests that pharmacogenomics has the potential to help clinicians improve the management of heart failure by choosing the safest and most effective medications and doses. Unfortunately, despite much supportive data, pharmacogenetic optimization of heart failure treatment regimens is not yet a reality. In order to attenuate the rising burden of heart failure, particularly in the context of the recent paucity of new effective interventions, there is an urgent need to extend pharmacogenetic knowledge and leverage these associations in order to enhance the effectiveness of existing heart failure therapies. This review focuses on the current state of pharmacogenomics in heart failure and provides a glimpse of the aforementioned future needs.