Clinical Practice Recommendations on Genetic Testing of CYP2C9 and VKORC1 Variants in Warfarin Therapy

QPGx-CARES: Qatar pharmacogenetics clinical applications and research enhancement strategies

Pharmacogenetic (PGx)-informed medication prescription is a cutting-edge genomic application in contemporary medicine, offering the potential to overcome the conventional "trial-and-error" approach in drug prescription. The ability to use an individual's genetic profile to predict drug responses allows for personalized drug and dosage selection, thereby enhancing the safety and efficacy of treatments. However, despite significant scientific and clinical advancements in PGx, its integration into routine healthcare practices remains limited. To address this gap, the Qatar Genome Program (QGP) has embarked on an ambitious initiative known as QPGx-CARES (Qatar Pharmacogenetics Clinical Applications and Research Enhancement Strategies), which aims to set a roadmap for optimizing PGx research and clinical implementation on a national scale. The goal of QPGx-CARES initiative is to integrate PGx testing into clinical settings with the aim of improving patient health outcomes. In 2022, QGP initiated several implementation projects in various clinical settings. These projects aimed to evaluate the clinical utility of PGx testing, gather valuable insights into the effective dissemination of PGx data to healthcare professionals and patients, and identify the gaps and the challenges for wider adoption. QPGx-CARES strategy aimed to integrate evidence-based PGx findings into clinical practice, focusing on implementing PGx testing for cardiovascular medications, supported by robust scientific evidence. The current initiative sets a precedent for the nationwide implementation of precision medicine across diverse clinical domains.

Using machine learning to predict the bleeding risk for patients with cardiac valve replacement treated with warfarin in hospitalized

BACKGROUND

Distinguishing warfarin-related bleeding risk at the bedside remains challenging. Studies indicate that warfarin therapy should be suspended when international normalized ratio (INR) ≥ 4.5, or it may sharply increase the risk of bleeding. We aim to develop and validate a model to predict the high bleeding risk in valve replacement patients during hospitalization.

METHOD

Cardiac valve replacement patients from January 2016 to December 2021 across Nanjing First Hospital were collected. Five different machine-learning (ML) models were used to establish the prediction model. High bleeding risk was an INR ≥4.5. The area under the receiver operating characteristic curve (AUC) was used for evaluating the prediction performance of different models. The SHapley Additive exPlanations (SHAP) was used for interpreting the model. We also compared ML with ATRIA score and ORBIT score.

RESULTS

A total of 2376 patients were finally enrolled in this model, 131 (5.5%) of whom experienced the high bleeding risk after anticoagulation therapy of warfarin during hospitalization. The extreme gradient boosting (XGBoost) exhibited the best overall prediction performance (AUC: 0.882, confidence interval [CI] 0.817-0.946, Brier score, 0.158) compared to other prediction models. It also shows superior performance compared with ATRIA score and ORBIT score. The top 5 most influential features in XGBoost model were platelet, thyroid stimulation hormone, body surface area, serum creatinine and white blood cell.

CONCLUSION

A model for predicting high bleeding risk in valve replacement patients who treated with warfarin during hospitalization was successfully developed by using machine learning, which may well assist clinicians to identify patients at high risk of bleeding and allow timely adjust therapeutic strategies in evaluating individual patient.

Safety Issues of Herb-Warfarin Interactions

Warfarin is a popular anticoagulant with high global demand. However, studies have underlined serious safety issues when warfarin is consumed concomitantly with herbs or its formulations. This review aimed to highlight the mechanisms behind herb-warfarin interactions while laying special emphasis on its PKPD interactions and evidence on Herb-Warfarin Interaction (HWI) with regards to three different scenarios, such as when warfarin is consumed with herbs, taken as foods or prescribed as medicine, or when used in special situations. A targeted literature methodology involving different scientific databases was adopted for acquiring information on the subject of HWIs. Results of the present study revealed some of the fatal consequences of HWI, including post-operative bleeding, thrombosis, subarachnoid hemorrhage, and subdural hematomas occurring as a result of interactions between warfarin and herbs or commonly associated food products from Hypericum perforatum, Zingiber officinale, Vaccinium oxycoccos, Citrus paradisi, and Punica granatum. In terms of PK-PD parameters, herbs, such as Coptis chinensis Franch. and Phellodendron amurense Rupr., were found to compete with warfarin for binding with plasma proteins, leading to an increase in free warfarin levels in the bloodstream, resulting in its augmented antithrombic effect. Besides, HWIs were also found to decrease International Normalised Ratio (INR) levels following the consumption of Persea americana or avocado. Therefore, there is an urgent need for an up-to-date interaction database to educate patients and healthcare providers on these interactions, besides promoting the adoption of novel technologies, such as natural language processing, by healthcare professionals to guide them in making informed decisions to avoid HWIs.

The INGENIOUS trial: Impact of pharmacogenetic testing on adverse events in a pragmatic clinical trial

Adverse drug events (ADEs) account for a significant mortality, morbidity, and cost burden. Pharmacogenetic testing has the potential to reduce ADEs and inefficacy. The objective of this INGENIOUS trial (NCT02297126) analysis was to determine whether conducting and reporting pharmacogenetic panel testing impacts ADE frequency. The trial was a pragmatic, randomized controlled clinical trial, adapted as a propensity matched analysis in individuals (N = 2612) receiving a new prescription for one or more of 26 pharmacogenetic-actionable drugs across a community safety-net and academic health system. The intervention was a pharmacogenetic testing panel for 26 drugs with dosage and selection recommendations returned to the health record. The primary outcome was occurrence of ADEs within 1 year, according to modified Common Terminology Criteria for Adverse Events (CTCAE). In the propensity-matched analysis, 16.1% of individuals experienced any ADE within 1-year. Serious ADEs (CTCAE level ≥ 3) occurred in 3.2% of individuals. When combining all 26 drugs, no significant difference was observed between the pharmacogenetic testing and control arms for any ADE (Odds ratio 0.96, 95% CI: 0.78-1.18), serious ADEs (OR: 0.91, 95% CI: 0.58-1.40), or mortality (OR: 0.60, 95% CI: 0.28-1.21). However, sub-group analyses revealed a reduction in serious ADEs and death in individuals who underwent pharmacogenotyping for aripiprazole and serotonin or serotonin-norepinephrine reuptake inhibitors (OR 0.34, 95% CI: 0.12-0.85). In conclusion, no change in overall ADEs was observed after pharmacogenetic testing. However, limitations incurred during INGENIOUS likely affected the results. Future studies may consider preemptive, rather than reactive, pharmacogenetic panel testing.

Efficacy of Warfarin Therapy Guided by Pharmacogenetics: A Real-world Investigation Among Han Taiwanese

PURPOSE

The anticoagulation activity of warfarin in populations with CYP2C9, VKORC1, and CYP4F2 variants differs between individuals and is correlated with poor international normalized ratio (INR) control. Pharmacogenetics-guided warfarin dosing has been successfully developed for patients with genetic variations in recent years. However, few real-world data have been used to investigate the INR and warfarin dosage and the time to target INR. This study examined the largest collection of genetic and clinical real-world data related to warfarin to provide further evidence supporting the benefits of pharmacogenetics in clinical outcomes.

METHODS

We retrieved a total of 69,610 INR-warfarin records after the index date from 2,613 patients in the China Medical University Hospital database between January 2003 and December 2019. Each INR reading was obtained from the latest laboratory data after the hospital visit date. Patients with a history of malignant neoplasms or pregnancy before the index date were excluded, as were patients without data on INR measurements after the fifth day of prescription, genetic information, or gender variables. The primary outcomes were the INR and warfarin dosage during days 7, 14, 28, 56, and 84 after prescription. The secondary outcome was the time required to reach the INR ranges of 1.5 to 3.0 and >4.0.

FINDINGS

A total of 59,643 INR-warfarin records from 2188 patients were retrieved. The average INR was higher for homozygous carriers of the minor allele at CYP2C9 and VKORC1 during the first 7 days (1.83 [1.03] [CYP2C9*1] and 2.46 [1.44] [CYP2C9*3], P < 0.001; 1.39 [0.36] [rs9923231 G/G], 1.55 [0.79] [rs9923231 G/A], and 1.96 [1.13] [rs9923231 A/A], P < 0.001) than for the wild-type allele. These patients with variants required lower warfarin doses than those with the wild-type allele during the first 28 days. CYP4F2 variant patients seemed to require higher doses of warfarin than those in the wild-type group; however, no significant difference in the average INR was observed (1.95 [1.14] [homozygous V433 carriers], 1.78 [0.98] [heterozygous V433M carriers], and 1.66 [0.91] [homozygous M433 carriers], P = 0.016).

IMPLICATIONS

Our study indicates that genetic variants in the Han population may enhance warfarin responsiveness, which holds clinical relevance. An increased warfarin dosage was not linked to a shorter time to therapeutic INR between CYP4F2 variant patients and those with a wild-type allele. Assessing CYP2C9 and VKORC1 genetic polymorphisms before initiating warfarin treatment in real-world practice is essential for potentially vulnerable patients and is likely to optimize therapeutic dosing.

Developing Chinese race-specific warfarin dose prediction algorithms

BACKGROUND

Numerous genotype-guided warfarin dosing algorithms have been developed to individualize warfarin doses, but they can only explain 47-52% of the variability.

AIM

This study aimed to develop new warfarin algorithms suitable to predict the stable warfarin dose for the Chinese population and to compare their prediction performance with those of the most commonly used algorithms.

METHOD

Multiple linear regression analysis with the warfarin optimal dose (WOD), logarithm (log) WOD, 1/WOD, and [Formula: see text], respectively, as the dependent variables were performed to deduce a new warfarin algorithm (NEW-Warfarin). WOD was the stable dose that maintained the international normalized ratio (INR) within the target range (2.0-3.0). Three major genotype-guided warfarin dosing algorithms were selected and compared against NEW-Warfarin predictive performance using the mean absolute error (MAE). Furthermore, patients were divided into five groups according to warfarin indications [atrial fibrillation (AF), pulmonary embolism (PE), cardiac-related disease (CRD), deep vein thrombosis (DVT), and other diseases (OD)]. Multiple linear regression analyses were also performed for each group.

RESULTS

The regression equation with [Formula: see text] as the dependent variable had the highest coefficient of determination (R² = 0.489). The NEW-Warfarin had the best predictive accuracy compared to the three algorithms selected. Group analysis, according to indications, showed that the R² of the five groups were PE (0.902) > DVT (0.608) > CRD (0.569) > OD (0.436) > AF (0.424).

CONCLUSION

Dosing algorithms based on warfarin indications are more suitable for predicting warfarin doses. Our research provides a novel strategy to develop indication-specific warfarin dosing algorithms to improve the efficacy and safety of warfarin prescribing.

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 national survey of individualized pharmaceutical care practice in Chinese hospitals in 2019

Background: Individualized pharmaceutical care, which consists of therapeutic drug monitoring (TDM), pharmacogenetic (PGx) testing and pharmacist-managed clinic (PMC), is one of the most important trends in clinical pharmacy development in the future. While relevant studies in China were primarily single-center or regional. This study aims to explore the current status of individualized pharmaceutical care in China, find out the existing problems and provide references for its further development. Methods: An electronic questionnaire was used and national hospitals' pharmaceutical administration data from January to December 2019 were collected. The data were sorted into Excel for further statistical analysis. All analyses were descriptive. Results: The proportions of hospitals that performed TDM and PGx testing were 12.83% and 9.48%, respectively. The major responsible departments were the clinical laboratory and pharmacy department. External quality control was carried out in around 70% of hospitals for both TDM and PGx testing. More than half of hospitals provided TDM services for valproate sodium, digoxin, carbamazepine, vancomycin and cyclosporine. And an average of 6.84 drugs were performed TDM in 540 hospitals. Clopidogrel and warfarin were the top two drugs that performed PGx testing. As for the PMC, 10.03% of hospitals opened PMC, of which 60.00% had independent PMC. Approximately 80% of PMC services were free of charge. Conclusion: The development of individualized pharmaceutical care in China is still in the early stage. Different sectors have to coalesce to promote its implementation, including the appropriate education, coverage, reimbursement policies, high-quality evidence, data systems, health system processes and health policies, etc.

Optimizing warfarin dosing using deep reinforcement learning

Warfarin is a widely used anticoagulant, and has a narrow therapeutic range. Dosing of warfarin should be individualized, since slight overdosing or underdosing can have catastrophic or even fatal consequences. Despite much research on warfarin dosing, current dosing protocols do not live up to expectations, especially for patients sensitive to warfarin. We propose a deep reinforcement learning-based dosing model for warfarin. To overcome the issue of relatively small sample sizes in dosing trials, we use a Pharmacokinetic/ Pharmacodynamic (PK/PD) model of warfarin to simulate dose-responses of virtual patients. Applying the proposed algorithm on virtual test patients shows that this model outperforms a set of clinically accepted dosing protocols by a wide margin. We tested the robustness of our dosing protocol on a second PK/PD model and showed that its performance is comparable to the set of baseline protocols.

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Hyper-responsiveness to warfarin in a young patient with the VKORC1 -1639GA/CYP2C9*1*46 genotype: a case report

BACKGROUND

Warfarin is the most widely used oral anticoagulant; nevertheless, dosing of warfarin is problematic for clinicians worldwide. Inter-individual variability in response to warfarin is attributed to genetic as well as non-genetic factors. Pharmacogenomics studies have identified variants in CYP2C9 and VKORC1 genes as significant predictors of warfarin dose, however, phenotypes of rare variants are not well characterized.

CASE PRESENTATION

We report a case of hyper-responsiveness to warfarin in a 22-year-old outpatient with Crohn's disease who presented with a swollen, red, and painful left calf. Deep venous thrombosis (DVT) in the left lower extremity was confirmed via ultrasonography, and hence, anticoagulation therapy of heparin and concomitant warfarin was initiated. Warfarin dose of 7.5 mg/day was estimated by the physician based on clinical factors. Higher than the expected international normalized ratio (INR) value of 4.5 necessitated the reduction of the warfarin dose to 5 and eventually to 2.5 mg/day to reach a therapeutic INR value of 2.6. Pharmacogenetic profiling of the VKORC1 -1639G > A and CYP2C9 *2, *3, *4, *5, *8, *14, *20, *24, *26, *33, *40, *41, *42, *43, *45, *46, *55, *62, *63, *66, *68, *72, *73 and *78 revealed a VKORC1-1639GA/CYP2C9*1*46 genotype. The lower catalytic activity of the CYP2C9*46 (A149T) variant was previously reported in in vitro settings.

CONCLUSIONS

This is the first report on a case of warfarin hyper-responsive phenotype of a patient with the heterozygous CYP2C9*1*46 polymorphism.

Warfarin sensitivity is associated with increased hospital mortality in critically Ill patients

Background

Warfarin is a widely used anticoagulant with a narrow therapeutic index and large interpatient variability in the therapeutic dose. Warfarin sensitivity has been reported to be associated with increased incidence of international normalized ratio (INR) > 5. However, whether warfarin sensitivity is a risk factor for adverse outcomes in critically ill patients remains unknown. In the present study, we aimed to evaluate the utility of different machine learning algorithms for the prediction of warfarin sensitivity and to determine the impact of warfarin sensitivity on outcomes in critically ill patients.

Methods

Nine different machine learning algorithms for the prediction of warfarin sensitivity were tested in the International Warfarin Pharmacogenetic Consortium cohort and Easton cohort. Furthermore, a total of 7,647 critically ill patients was analyzed for warfarin sensitivity on in-hospital mortality by multivariable regression. Covariates that potentially confound the association were further adjusted using propensity score matching or inverse probability of treatment weighting.

Results

We found that logistic regression (AUC = 0.879, 95% CI: 0.834–0.924) was indistinguishable from support vector machine with a linear kernel, neural network, AdaBoost and light gradient boosting trees, and significantly outperformed all the other machine learning algorithms. Furthermore, we found that warfarin sensitivity predicted by the logistic regression model was significantly associated with worse in-hospital mortality in critically ill patients with an odds ratio (OR) of 1.33 (95% CI, 1.01–1.77).

Conclusions

Our data suggest that the logistic regression model is the best model for the prediction of warfarin sensitivity clinically and that warfarin sensitivity is likely to be a risk factor for adverse outcomes in critically ill 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.

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.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.

Phase 2 Study of the Factor XI Antisense Inhibitor IONIS-FXIRx in Patients With ESRD

Introduction

Patients with end-stage renal disease (ESRD) requiring hemodialysis (HD) have an increased risk of thrombotic events and bleeding. Antisense reduction of factor XI (FXI) with IONIS-FXI_Rx is a novel strategy that may safely reduce the risk of thrombotic events.

Methods

This multicenter study enrolled 49 patients receiving HD in 2 parts. First, 6 participants (pharmacokinetics [PK] cohort) received 1 open-label 300 mg dose of IONIS-FXI_Rx both before and after HD. Subsequently, 43 participants were treated in a double-blind, randomized design with 200 mg or 300 mg IONIS-FXI_Rx or placebo for 12 weeks. The PK, pharmacodynamics (PD), and adverse events of IONIS-FXI_Rx were evaluated (ClinicalTrials.gov: NCT02553889).

Results

The PK of IONIS-FXI_Rx was consistent with previous studies and similar whether injected before or after HD. No accumulation of IONIS-FXI_Rx was observed after repeat administration. By day 85, mean levels of FXI activity fell 56.0% in the 200 mg group, 70.7% in the 300 mg group, and 3.9% in the placebo group compared with baseline. FXI antigen levels paralleled FXI activity. Dose-dependent prolongation of activated partial thromboplastin time (aPTT) was observed, with no changes in international normalized ratio (INR). IONIS-FXI_Rx was not associated with drug-related serious adverse events. In the randomized phase of the study, major bleeding events occurred in 0 (0.0%; 200 mg), 1 (6.7%; 300 mg), and 1 (7.7%; placebo) patients and were not considered related to treatment.

Conclusion

IONIS-FXI_Rx reduced FXI activity in patients with ESRD receiving HD. Further studies are needed to determine the benefit-risk profile of FXI as a therapeutic target for patients who require HD.

Heart Failure Association of the European Society of Cardiology position paper on the management of left ventricular assist device-supported patients for the non-left ventricular assist device specialist healthcare provider: Part 2: at the emergency department

The improvement in left ventricular assist device (LVAD) technology and scarcity of donor hearts have increased dramatically the population of the LVAD‐supported patients and the probability of those patients to present to the emergency department with expected and non‐expected device‐related and patient–device interaction complications. The ageing of the LVAD‐supported patients, mainly those supported with the ‘destination therapy’ indication, increases the risk for those patients to suffer from other co‐morbidities common in the older population. In this second part of the trilogy on the management of LVAD‐supported patients for the non‐LVAD specialist healthcare provider, definitions and structured approach to the LVAD‐supported patient presenting to the emergency department with bleeding, neurological event, pump thrombosis, chest pain, syncope, and other events are presented. The very challenging issue of declaring death in an LVAD‐supported patient, as the circulation is artificially preserved by the device despite no other signs of life, is also discussed in detail.

Performance Evaluation of Warfarin Dose Prediction Algorithms and Effects of Clinical Factors on Warfarin Dose in Chinese Patients

BACKGROUND

The clinical utility of warfarin dose prediction algorithms remains controversial, our purpose is to evaluate the performance of warfarin dose prediction algorithms and the effects of clinical factors on warfarin dose in Chinese patients.

METHODS

Clinical data of 217 patients who received warfarin treatment were used to assess 6 warfarin dose prediction algorithms (OHNO, IWPC [International Warfarin Pharmacogenetics Consortium], HUANG, KIM, BRESS, and MIAO). The predicted dose (PD) was compared with the warfarin optimal dose (WOD, defined as the dose that maintains the international normalized ratio within the target range of 2.0-3.0). A multiple regression analysis with WOD as the dependent variable was performed to evaluate the effects of clinical factors on warfarin dose.

RESULTS

The mean absolute error analysis ranked the predictive accuracies of the algorithms as OHNO > IWPC > HUANG > KIM > BRESS > MIAO. Stratified analysis indicated that HUANG most accurately predicted that patients required lower WODs (≤3 mg/d), whereas OHNO was the most effective in predicting medium WODs (3-5 mg/d). KIM was effective in predicting high WODs (>5 mg/d). Multiple linear regression analysis showed that VKORC1 (rs9923231) and body mass index were significantly positively correlated with WOD, whereas concurrent atrial fibrillation status, CYP2C9*3 (rs1057910), and sex were significantly negatively correlated with WOD.

CONCLUSIONS

In Chinese patients, OHNO should be given priority during the prediction and selection of warfarin dose. When using OHNO to predict warfarin dose (≤3 mg/d or >5 mg/d), HUANG or KIM algorithms can provide precise predictions. At the same time, physicians should pay close attention to clinical factors, such as VKORC1 (rs9923231), concurrent atrial fibrillation status, CYP2C9*3 (rs1057910), body mass index, and sex, to improve warfarin dose adjustment strategies in Chinese patients.

Access to precision medicine in Thailand: a comparative study

Purpose

This study explored health insurance coverage of genetic testing and potential factors associated with precision medicine (PM) reimbursement in Thailand.

Design/methodology/approach

The study employed a targeted review method. Thirteen PMs were selected to represent four PM categories: targeted cancer therapy candidate, prediction of adverse drug reactions (ADRs), dose adjustment and cancer risk prediction. Content analysis was performed to compare access to PMs among three health insurance schemes in Thailand. The primary outcome of the study was evaluating PM test reimbursement status. Secondary outcomes included clinical practice guidelines, PMs statement in FDA-approved leaflet and economic evaluation.

Findings

Civil Servant Medical Benefits Scheme (CSMBS) provided more generous access to PM than Universal Coverage Scheme (UCS) and Social Security Scheme (SSS). Evidence of economic evaluations likely impacted the reimbursement decisions of SSS and UCS, while the information provided in FDA-approved leaflets seemed to impact the reimbursement decisions of CSMBS. Three health insurance schemes provided adequate access to PM tests for some cancer-targeted therapies, while gaps existed for access to PM tests for serious ADRs prevention, dose adjustment and cancer risk prediction.

Originality/value

This was the first study to explore the situation of access to PMs in Thailand. The evidence alerts public health insurance schemes to reconsider access to PMs. Development of health technology assessment guidelines for PM test reimbursement decisions should be prioritized.

An ensemble learning based framework to estimate warfarin maintenance dose with cross-over variables exploration on incomplete data set

MOTIVATION

Warfarin is a widely used oral anticoagulant, but it is challenging to select the optimal maintenance dose due to its narrow therapeutic window and complex individual factor relationships. In recent years, machine learning techniques have been widely applied for warfarin dose prediction. However, the model performance always meets the upper limit due to the ignoration of exploring the variable interactions sufficiently. More importantly, there is no efficient way to resolve missing values when predicting the optimal warfarin maintenance dose.

METHODS

Using an observational cohort from the Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, we propose a novel method for warfarin maintenance dose prediction, which is capable of assessing variable interactions and dealing with missing values naturally. Specifically, we examine single variables by univariate analysis initially, and only statistically significant variables are included. We then propose a novel feature engineering method on them to generate the cross-over variables automatically. Their impacts are evaluated by stepwise regression, and only the significant ones are selected. Lastly, we implement an ensemble learning based approach, LightGBM, to learn from incomplete data directly on the selected single and cross-over variables for dosing prediction.

RESULTS

377 unique patients with eligible and time-independent 1173 warfarin order events are included in this study. Through the comprehensive experimental results in 5-fold cross-validation, our proposed method demonstrates the efficiency of exploring the variable interactions and modeling on incomplete data. The R² can achieve 75.0% on average. Moreover, the subgroup analysis results reveal that our method performs much better than other baseline methods, especially in the medium-dose and high-dose subgroups. Lastly, the IWPC dosing prediction model is used for further comparison, and our approach outperforms it by a significant margin.

CONCLUSION

In summary, our proposed method is capable of exploring the variable interactions and learning from incomplete data directly for warfarin maintenance dose prediction, which has a great premise and is worthy of further research.

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.

Identification of high-impact gene-drug pairs for pharmacogenetic testing in Alberta, Canada

OBJECTIVES

To facilitate decision-making and priority-setting related to Alberta's Pharmacogenomics (PGx) testing implementation strategy by identifying gene-drug pairs with the highest potential impact on prescribing practices in Alberta.

PATIENTS AND METHODS

Annual drug dispensing data for Alberta from 2012 to 2016 for 57 medications with PGx-based prescribing guidelines were obtained, along with population estimates and demographics (age and ethnicity). Frequencies of actionable PGx genotypes by ethnicity were obtained from the Pharmacogenomics Knowledgebase (PharmGKB). Annual dispensing activity for each of the 57 medications was calculated for the full population (all ages) and children/youth (0-19 years). Alberta ethnicity data were cross-referenced with genetic frequency data for each of the main ethnic groups from PharmGKB to estimate the proportion of individuals with actionable genotypes. Actionable genotype proportions and drug dispensing frequencies were collectively used to identify high impact gene-drug pairs.

RESULTS

We found (a) half of the drugs with PGx-based prescribing guidelines, namely, analgesics, proton pump inhibitors, psychotropics, and cardiovascular drugs, were dispensed at high frequencies (>1% of the entire population), (b) the dispensing rate for about one-third of these drugs increased over the 5-year study period, (c) between 1.1 and 45% of recipients of these drugs carried actionable genotypes, and (d) the gene-drug pairs with greatest impact in Alberta predominatly included CYP2C19 or CYP2D6.

CONCLUSIONS

We uncovered specific patterns in drug dispensing and identified important gene-drug pairs that will inform the planning and development of an evidenced-based PGx testing service in Alberta, Canada. Adaptation of our approach may facilitate the process of evidence-based PGx testing implementation in other jurisdictions.

Synthesis of major pharmacogenomics pretest counseling themes: a multisite comparison

The accessibility of pharmacogenomic (PGx) testing has grown substantially over the last decade and with it has arisen a demand for patients to be counseled on the use of these tests. While guidelines exist for the use of PGx results; objective determinants for who should receive PGx testing remain incomplete. PGx clinical services have been created to meet these screening and education needs and significant variability exists between these programs. This article describes the practices of four PGx clinics during pretest counseling sessions. A description of the major tenets of the benefits, limitations and risks of testing are compiled. Additional tools are provided to serve as a foundation for those wishing to begin or expand their own counseling service.

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.

The art and science of drug titration

A “one-size-fits-all” approach has been the standard for drug dosing, in particular for agents with a wide therapeutic index. The scientific principles of drug titration, most commonly used for medications with a narrow therapeutic index, are to give the patient adequate and effective treatment, at the lowest dose possible, with the aim of minimizing unnecessary medication use and side effects. The art of drug titration involves the interplay of scientific drug titration principles with the clinical expertise of the healthcare provider, and an individualized, patient-centered partnership between the provider and the patient to review the delicate balance of perceived benefits and risks from both perspectives. Drug titration may occur as up-, down-, or cross-titration depending on whether the goal is to reach or maintain a therapeutic outcome, decrease the risk of adverse effects, or prevent withdrawal/discontinuation syndromes or recurrence of disease. Drug titration introduces additional complexities surrounding the conduct of clinical trials and real-world studies, confounding our understanding of the true effect of medications. In clinical practice, wide variations in titration schedules may exist due to a lack of evidence and consensus on titration approaches that achieve an optimal benefit-harm profile. Further, drug titration may be challenging for patients to follow, resulting in suboptimal adherence and may require increased healthcare-related visits and coordination of care amongst providers. Despite the challenges associated with drug titration, it is a personalized approach to drug dosing that blends science with art, and with supportive real-world outcomes-based evidence, can be effective for optimizing pharmacotherapeutic outcomes and improving drug safety.

Association Between the Prothrombin Time–International Normalized Ratio and Concomitant Use of Antibiotics in Warfarin Users: Focus on Type of Antibiotic and Susceptibility of Bacteroides fragilis to Antibiotics

Background:

The difference in type of antibiotics and susceptibility of Bacteroides fragilis to antibiotics may influence warfarin anticoagulation. However, these influences have not been clarified in clinical settings.

Objectives:

This study aimed to investigate association the between the prothrombin time–international normalized ratio (PT-INR) and concomitant use of antibiotics in a real-world population of warfarin users.

Methods:

This was a single-center cohort study using data from health records and included patients who received β-lactams (BLs)/fluoroquinolones (FQs) during ongoing warfarin treatment (2011-2015) at Hamamatsu University Hospital in Japan. Antibiotics were categorized into those to which B fragilis is susceptible (BLsus, FQsus) and those to which it is not (BLnon, FQnon) and into those given orally (BLpo, FQpo) or intravenously (BLiv, FQiv). Outcomes were excessive PT-INR and changes in PT-INR, defined as the ratio (INR ratio) and difference (ΔINR) of maximum PT-INR and baseline PT-INR. Excessive PT-INR was graded as INR ratio of >1.5 or >2.5.

Results:

A total of 1185 warfarin users were included. The proportion of INR ratio >2.5 in FQiv was higher than in BLiv (95% CI: 1.59-46.5). The proportions with an INR ratio of >1.5 in BLsus and FQsus were higher than in BLnon (1.72-14.1) and FQnon (1.05-9.36), respectively. ΔINR values in FQpo, FQiv, and FQsus were higher than those in BLpo, BLiv, and FQnon, respectively.

Conclusions and Relevance:

Concomitant use of FQs, or of antibiotics to which B fragilis is susceptible is associated with higher risk of excessive anticoagulation. These findings would contribute to safe and proper antibiotic treatment in warfarin users.

Development and Validation of a Novel Warfarin Dosing Algorithm for Korean Patients With VKORC1 1173C

BACKGROUND

Differences in the performance of suggested warfarin dosing algorithms among different ethnicities and genotypes have been reported; this necessitates the development of an algorithm with enhanced performance for specific population groups. Previous warfarin dosing algorithms underestimated warfarin doses in VKORC1 1173C carriers. We aimed to develop and validate a new warfarin dosing algorithm for Korean patients with VKORC1 1173C.

METHODS

A total of 109 patients carrying VKORC1 1173CT (N=105) or 1173CC (N=4) were included in this study. Multiple regression analysis was performed to deduce a new dosing algorithm. Following literature searches for genotype-guided warfarin dosing algorithms, 21 algorithms were selected and evaluated using the correlation coefficient (ρ) of actual dose and estimated dose, mean error, and root mean square error.

RESULTS

The developed algorithm is as follows: maintenance dose (mg/week)=exp [3.223-0.009×(age)+0.577×(body surface area [BSA])+0.178×(sex)-0.481×(CYP2C9 genotype)+0.227×(VKORC1 genotype)]. Integrated variables explained 44% of the variance in the maintenance dose. The predicted and actual doses showed moderate correlation (ρ=0.641) with the best performance with a mean error of -1.30 mg/week. The proportion of underestimated groups was 17%, which was lower than with the other algorithms.

CONCLUSIONS

This is the first study to develop and validate a warfarin dosing algorithm based on data from VKORC1 1173C carriers; it showed superior predictive performance compared with previously published algorithms.

Recommendations for Clinical Warfarin Genotyping Allele Selection: A Report of the Association for Molecular Pathology and the College of American Pathologists

The goal of the Association for Molecular Pathology (AMP) Clinical Practice Committee's AMP Pharmacogenomics (PGx) Working Group is to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The AMP PGx Working Group considered functional impact of the variants, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations for PGx testing when developing these recommendations. The ultimate goal is to promote standardization of PGx gene/allele testing across clinical laboratories. These recommendations are not to be interpreted as prescriptive but to provide a reference guide. Of note, a separate article with recommendations for CYP2C9 allele selection was previously developed by the PGx Working Group that can be applied broadly to CYP2C9-related medications. The warfarin allele recommendations in this report incorporate the previous CYP2C9 allele recommendations and additional genes and alleles that are specific to warfarin testing.

Integration analysis of metabolites and single nucleotide polymorphisms improves the prediction of drug response of celecoxib

INTRODUCTION

Pharmacogenetics and pharmacometabolomics are the common methods for personalized medicine, either genetic or metabolic biomarkers have limited predictive power for drug response.

OBJECTIVES

In order to better predict drug response, the study attempted to integrate genetic and metabolic biomarkers for drug pharmacokinetics prediction.

METHODS

The study chose celecoxib as study object, the pharmacokinetic behavior of celecoxib was assessed in 48 healthy volunteers based on UPLC-MS/MS platform, and celecoxib related single nucleotide polymorphisms (SNPs) were also detected. Three mathematic models were constructed for celecoxib pharmacokinetics prediction, the first one was mainly based on celecoxib-related SNPs; the second was based on the metabolites selected from a pharmacometabolomic analysis by using GC-MS/MS method, the last model was based on the combination of the celecoxib-related SNPs and metabolites above.

RESULTS

The result proved that the last model showed an improved prediction power, the integration model could explain 71.0% AUC variation and predict 62.3% AUC variation. To facilitate clinical application, ten potential celecoxib-related biomarkers were further screened, which could explain 68.3% and predict 54.6% AUC variation, the predicted AUC was well correlated with the measured values (r = 0.838).

CONCLUSION

This study provides a new route for personalized medicine, the integration of genetic and metabolic biomarkers can predict drug response with a higher accuracy.

Clinical Model for Predicting Warfarin Sensitivity

Warfarin is a widely used anticoagulant with a narrow therapeutic index and large interpatient variability in the therapeutic dose. Complications from inappropriate warfarin dosing are one of the most common reasons for emergency room visits. Approximately one third of warfarin dose variability results from common genetic variants. Therefore, it is very necessary to recognize warfarin sensitivity in individuals caused by genetic variants. Based on combined polymorphisms in CYP2C9 and VKORC1, we established a clinical classification for warfarin sensitivity. In the International Warfarin Pharmacogenetic Consortium (IWPC) with 5542 patients, we found that 95.1% of the Black in the IWPC cohort were normal warfarin responders, while 74.8% of the Asian were warfarin sensitive (P < 0.001). Moreover, we created a clinical algorithm to predict warfarin sensitivity in individual patients using logistic regression. Compared to a fixed-dose approach, the clinical algorithm provided significantly better performance. In addition, we validated the derived clinical algorithm using the external Easton cohort with 106 chronic warfarin users. The AUC was 0.836 vs. 0.867 for the Easton cohort and the IWPC cohort, respectively. With the use of this algorithm, it is very likely to facilitate patient care regarding warfarin therapy, thereby improving clinical outcomes.

Pharmacogenomic Testing: Clinical Evidence and Implementation Challenges

Pharmacogenomics can enhance patient care by enabling treatments tailored to genetic make-up and lowering risk of serious adverse events. As of June 2019, there are 132 pharmacogenomic dosing guidelines for 99 drugs and pharmacogenomic information is included in 309 medication labels. Recently, the technology for identifying individual-specific genetic variants (genotyping) has become more accessible. Next generation sequencing (NGS) is a cost-effective option for genotyping patients at many pharmacogenomic loci simultaneously, and guidelines for implementation of these data are available from organizations such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG). NGS and related technologies are increasing knowledge in the research sphere, yet rates of genomic literacy remain low, resulting in a widening gap in knowledge translation to the patient. Multidisciplinary teams—including physicians, nurses, genetic counsellors, and pharmacists—will need to combine their expertise to deliver optimal pharmacogenomically-informed care.

Pharmacogenetics in the Treatment of Cardiovascular Diseases and Its Current Progress Regarding Implementation in the Clinical Routine

There is a special interest in the implementation of pharmacogenetics in clinical practice, although there are some barriers that are preventing this integration. A large part of these pharmacogenetic tests are focused on drugs used in oncology and psychiatry fields and for antiviral drugs. However, the scientific evidence is also high for other drugs used in other medical areas, for example, in cardiology. In this article, we discuss the evidence and guidelines currently available on pharmacogenetics for clopidogrel, warfarin, acenocoumarol, and simvastatin and its implementation in daily clinical practice.

Precision dosing of warfarin: open questions and strategies

Warfarin has a very narrow therapeutic window and obvious interindividual variability in its effects, with many factors contributing to the body's response. Algorithms incorporating multiple genetic, environment and clinical factors have been established to select a precision dose for each patient. A number of randomized controlled trials (RCTs) were conducted to explore whether patients could benefit from these algorithms; however, the results were inconsistent. Some questions remain to be resolved. Recently, new genetic and non-genetic factors have been discovered to contribute to variability in optimal warfarin doses. The results of further RCTs have been unveiled, and guidelines for pharmacogenetically guided warfarin dosing have been updated. Based on these most recent advancements, we summarize some open questions in this field and try to propose possible strategies to resolve them.

Association between polymorphisms of VKORC1 and CYP2C9 genes with warfarin maintenance dose in a group of warfarin users in Birjand city, Iran

Warfarin is the cardinal anticoagulant drug prescribed around the world. Due to stochastic bleeding in patients, it is essential to adjust the dose for every individual. The aim of the present study was to evaluate the frequency of CYP2C9 and VKORC1 gene polymorphisms and their association with warfarin maintenance dose in a sample of cardiovascular patients in Birjand, South-Khorasan province of Iran. Patients with a history of cardiovascular disorders who take warfarin daily were selected. CYP2C9 and VKORC1 gene polymorphisms were detected by polymerase chain reaction-restriction fragment length polymorphism in all participants. A total of 114 patients (mean age: 52.7 ± 14.9 years, M/F ratio: 0.76) participated in this study. Regarding CYP2C9 gene polymorphisms, the most frequent genotype was 1*/1* (80.4% in females and 62.5% in males). The frequency of 1*/2* and 2*/2* variants was 13% and 6.5% in females and 25% and 12.5% in males, respectively. The frequency of VKORC1 gene (1639 G > A), was 31.5%, 39.5%, and 29% for GG, GA, and AA in males, respectively. Besides, the mentioned genotype frequencies for females were 50%, 40.5%, and 9.5%, respectively. Moreover, there was a statistically significant correlation between VKORC1 gene -1639 G > A variant and warfarin maintenance dose (P < 0.001) but not for CYP2C9 variants. The results of the current study confirmed that the mutant variants of CYP2C9 are not frequent and do not have any impact on warfarin dose. In the case of VKORC1, the mutant allele (A) showed a positive correlation with warfarin dose adjustment.

Analyses of Adverse Drug Reactions-Nationwide Active Surveillance Network: Canadian Pharmacogenomics Network for Drug Safety Database

Adverse drug reactions (ADRs) are a major problem in modern medicine, representing up to the fourth-highest cause of mortality. Pharmacogenomic tests are 1 of the most promising methods to tackle the challenge of ADRs. The objective of this study was to analyze the clinical and demographic information of the pan-Canadian active surveillance network, Canadian Pharmacogenomics Network for Drug Safety (CPNDS). Information entered into the database by trained active surveillors between May 15, 2005 and May 9, 2017 was collected and analyzed. Specific data included for analysis were number of ADR reports, reports of drug use without ADRs, date of onset of ADR, suspected drugs, concomitant drugs, and fatal ADR cases. The CPNDS database consisted of 93,974 reports of medication use, including 10,475 reports of ADRs, of which 72.6% occurred in pediatric patients (≤21 years old). Self-reported ancestries were predominantly Europe (38.2%), Canada (9.6%), and East Asia (4.9%). The 5 most frequent ADRs were cutaneous ADRs, peripheral neuropathy, cardiotoxicity, central nervous system toxicity, and ototoxicity. The 5 drugs most commonly suspected to cause ADRs were methotrexate, vincristine, doxorubicin, cisplatin, and L-asparaginase. The CPNDS database is a valuable resource to identify clinical and genomic predictors of ADRs. The database also highlights our candidate ADRs for pharmacogenomic discovery research to identify additional ADR biomarkers. Additionally, the database provides information that can be used for developing strategies to prevent ADRs and raises awareness of ADRs among Canadian healthcare professionals.

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose

Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with devastating adverse events. Remarkable efforts have been made to develop the machine learning based warfarin dosing algorithms incorporating clinical factors and genetic variants such as polymorphisms in CYP2C9 and VKORC1. The most widely validated pharmacogenetic algorithm is the IWPC algorithm based on multivariate linear regression (MLR). However, with only a single algorithm, the prediction performance may reach an upper limit even with optimal parameters. Here, we present novel algorithms using stacked generalization frameworks to estimate the warfarin dose, within which different types of machine learning algorithms function together through a meta-machine learning model to maximize the prediction accuracy. Compared to the IWPC-derived MLR algorithm, Stack 1 and 2 based on stacked generalization frameworks performed significantly better overall. Subgroup analysis revealed that the mean of the percentage of patients whose predicted dose of warfarin within 20% of the actual stable therapeutic dose (mean percentage within 20%) for Stack 1 was improved by 12.7% (from 42.47% to 47.86%) in Asians and by 13.5% (from 22.08% to 25.05%) in the low-dose group compared to that for MLR, respectively. These data suggest that our algorithms would especially benefit patients requiring low warfarin maintenance dose, as subtle changes in warfarin dose could lead to adverse clinical events (thrombosis or bleeding) in patients with low dose. Our study offers novel pharmacogenetic algorithms for clinical trials and practice.

Creating and validating a warfarin pharmacogenetic dosing algorithm for Colombian patients

Purpose

Warfarin is an oral anticoagulant associated with adverse reaction to drugs due to wide inter- and intra-individual dosage variability. Warfarin dosage has been related to non-genetic and genetic factors. CYP2C9 and VKORC1 gene polymorphisms affect warfarin metabolism and dosage. Due to the central role of populations’ ethnical and genetic origin on warfarin dosage variability, novel algorithms for Latin American subgroups are necessary to establish safe anticoagulation therapy.

Patients and methods

We genotyped CYP2C9*2 (c.430C > T), CYP2C9*3 (c.1075A > C), CYP4F2 (c.1297G > A), and VKORC1 (−1639 G > A) polymorphisms in 152 Colombian patients who received warfarin. We evaluated the impact on the variability of patients’ warfarin dose requirements. Multiple linear regression analysis, using genetic and non-genetic variables, was used for creating an algorithm for optimal warfarin maintenance dose.

Results

Median weekly prescribed warfarin dosage was significantly lower in patients having the VKORC1-1639 AA genotype and poor CYP2C9*2/*2,*2/*3 metabolizers than their wild-type counterparts. We found a 2.3-fold increase in mean dose for normal sensitivity patients (wild-type VKORC1/CYP2C9 genotypes) compared to the other groups (moderate and high sensitivity); 31.5% of the patients in our study group had warfarin sensitivity-related genotypes. The estimated regression equation accounted for 44.4% of overall variability in regard to warfarin maintenance dose. The algorithm was validated, giving 45.9% correlation (R²=0.459).

Conclusion

Our results describe and validate the first algorithm for predicting warfarin maintenance in a Colombian mestizo population and have contributed toward the understanding of pharmacogenetics in a Latin American population subgroup.

Establishment of a Han Chinese-specific pharmacogenetic-guided warfarin dosing algorithm

Warfarin is the most common oral anticoagulant. Because of a narrow therapeutic range, interindividual differences in drug responses, and the risk of bleeding, there are many challenges in using warfarin. We need to predict the warfarin maintenance dose. However, ethnic-specific algorithms may be required, and some Chinese algorithms do not perform adequately. Therefore, we aimed to establish a Han Chinese appropriate algorithm.We recruited a study group consisting of 361 Han Chinese patients receiving warfarin treatment who had heart valve replacements. Genotyping of 38 single nucleotide polymorphisms (SNPs) in 13 candidate genes was carried out using the MassARRAY. In the derivation cohort, a multiple linear regression model was constructed to predict the warfarin dosage. We evaluated the accuracy of our algorithm in the validation cohort and compared it with the other 5 algorithms based on Han Chinese and other races.We established a Han Chinese-specific pharmacogenetic-guided warfarin dosing algorithm. Warfarin maintenance dosage (mg/day) = 1.787 - 0.023 × (Age) + 1.151 × (BSA [m]) + 0.917 × (VKORC1 AG) + 4.619 × (VKORC1 GG) + 0.595 × (CYP4F2 TT) + 0.707 × (CYP2C19 CC). It explained 58.3% of the variance in warfarin doses in Han Chinese patients and was superior to the other 5 algorithms. The ability of the 6 algorithms which estimate the required dose correctly was tested. Our model had a mean absolute error of 0.74 mg/day, the other 5 models have mean absolute error of 0.81 mg/day,1.05 mg/day, 1.24 mg/day, 1.18 mg/day, and 0.85 mg/day, respectively. Our model had a mean percentage error of 26.9%, the other 5 models have the mean percentage error of 27.7%, 27.2%, 52.3%, 45.7%, and 29.3%, respectively.Physicians can not adopt algorithm from other race directly to predict warfarin dose in patients with heart valve replacements, they should establish a new algorithm or adjust another algorithm to fit their patients. The algorithm established in this study has the potential to assist physicians in determining warfarin doses that are close to the appropriate doses.

Weight and the vitamin K expoxide reductase 1 genotype primarily contribute to the warfarin dosing in pediatric patients with Kawasaki disease

INTRODUCTION

Warfarin therapy is recommended in children with giant coronary artery aneurysms (GCAAs) after Kawasaki disease (KD). Large individual variability makes it difficult to predict the warfarin dose. Polymorphisms in the vitamin K expoxide reductase 1 (VKORC1) and cytochrome P4502C9 (CYP2C9) genes have been reported to influence the warfarin dose. We investigated the effects of the VKORC1 and CYP2C9 genotypes on the warfarin dose in pediatric patients with giant CAAs after KD. We attempted to create a dosing algorithm.

MATERIALS AND METHODS

The clinical and genetic data of patients were documented. VKORC1 (rs 9923231) and CYP2C9 *3 (rs 1057910) were genotyped using TaqMan real-time polymerase chain reaction. A linear regression analysis was performed to evaluate the contribution of clinical and genetic factors to the warfarin maintenance dose.

RESULTS

Forty-seven patients were enrolled. Patients with the CT or CC genotype of VKORC1 had a relatively higher warfarin dose than did those with the TT genotype (p < 0.05). Three patients with CYP2C9*1/*3 had a lower warfarin dose than did those with the wild CYP2C9*1/*1 genotype, but the difference did not reach significance (p > 0.05). Weight and the VKORC1 genotype predominantly contributed to the warfarin dose, with 33.0% and 11.2% of variability, respectively. The observed warfarin dose was correlated with the predicted dose based on the algorithm used in our study (r = 0.45, p < 0.01).

CONCLUSIONS

Weight and the VKORC1 genotype primarily determined the warfarin dose in Chinese pediatric patients with KD. Further studies are warranted to verify the findings of our study.

Evaluation of CYP2C9- and VKORC1-based pharmacogenetic algorithm for warfarin dose in Gaza-Palestine

Aim

To evaluate applicability of CYP2C9*2, *3 and VKORC1-1639G > A based algorithm to predict warfarin stable dose (WSD) in a group of Palestinian patients.

Patients & methods

Warfarin doses were retrospectively calculated for 101 Palestinian patients under warfarin therapy using three models. Performance of the three models was assessed in 47 patients found to take WSD.

Results

Frequency of CYP2C9*2, *3 and VKORC1-1639G > A alleles is 13.6, 0.0 and 46.5% respectively. The international warfarin pharmacogenetics consortium algorithm was more reliable (MAE = 8.9 ± 1.4; R² = 0.350) than both the clinical algorithm (MAE = 10.4 ± 1.4; R² = 0.128;) and the fixed-dose algorithm (MAE = 11.1 ± 1.7).

Conclusion

The international warfarin pharmacogenetics consortium algorithm can be reliably applied for predicting the WSD in Palestinian population.

The rs2108622 polymorphism is related to the early risk of ischemic stroke in non-valvular atrial fibrillation subjects under oral anticoagulation

Oral anticoagulant treatments, such as vitamin K antagonists (VKAs), are the main treatments administered to atrial fibrillation (AF) patients in order to prevent ischemic stroke (IS). However, the genes involved in the VKA metabolism can undergo variations in a single nucleotide (SNP). These SNPs may then affect the VKA target enzyme (VKORC1), VKA degradation enzyme (CYP2C9), and vitamin K bioavailability enzyme (CYP4F2). We genotyped these SNPs in a cohort of patients with non-valvular AF who were under VKA treatment after suffering an IS. Clinical variables, CHADS2-VASC score and data about the international normalized ratio (INR) within the therapeutic range were all recorded. DNA was extracted from blood and genotyping was carried out by DNA sequencing. The main endpoint was the time from VKA onset to IS. Of a total of 356 consecutive IS patients monitored, 33 were included in the study. The median time to the event was 2248.0 days (interquartile range [IQR] 896.3-3545.3). The median CHADS2-VASC score was 4.0 (IQR 3.0-6.0). When we considered the risk of IS within 2 years under VKA treatment, we found that only the rs2108622 AA genotype was significantly associated with this endpoint (early IS) (hazard ratio 6.81, 95% CI 1.37-33.92, p = 0.019). Kaplan-Meier curve analysis also showed a significant relationship between early IS and rs2108622 AA genotype (Log rank p = 0.022). The CYP4F2 gene rs2108622 polymorphism was associated with a risk of early IS in NV-AF patients under VKA treatment.

UNUSUAL WARFARIN DOSE TO ACHIEVE THERAPEUTIC INR IN A 4-MONTH OLD CHILD: NON-GENETICS RISK FACTORS ARE STILL A CHALLENGE

Objective:

To report a case of a 4-month old girl that required 0.7 mg/kg/day (5 mg) of warfarin and discuss relevant risk factors for requiring higher doses.

Case Description:

In November 2015, a 5 kg female infant (36-week preterm) was admitted to the hospital due to status epilepticus and fever. Diazepam, phenytoin and ceftriaxone were prescribed. Cerebrospinal fluid contained 7 leukocytes, 150 mg/dL proteins, 1 mg/dL glucose and gram positive cocci were observed. Cranial tomography suggested hypodense signs in the cerebellum, right temporal lobe and left basal nuclei, which was consistent with pneumococcal meningitis-induced infectious vasculitis. She required low molecular weight heparin and warfarin for post-encephalitis thrombosis. About 10 days were required to achieve therapeutic INR, and warfarin was adjusted five times since the initial prescription.

Comments:

The risk factors for higher warfarin doses were age and enteral tube feeding. Phenobarbital and prednisone might also have contributed with one of the highest warfarin dose ever reported. Despite current importance given to genetics testing, clinicians should attempt to identify common contributing factors for prolonged non-therapeutic INR, to minimize the risk of coagulation, and to reduce costs of hospital stay and laboratory exams.

Long-term outcomes of elderly patients with CYP2C9 and VKORC1 variants treated with vitamin K antagonists

Essentials The long-term effects of VKORC1 and CYP2C9 variants on clinical outcomes remains unclear. We followed 774 patients ≥65 years with venous thromboembolism for a median duration of 30 months. Patients with CYP2C9 variants are at increased risk of death and non-major bleeding. Patients with genetic variants have a slightly lower anticoagulation quality only.

SUMMARY

Background The long-term effect of polymorphisms of the vitamin K-epoxide reductase (VKORC1) and the cytochrome P450 enzyme gene (CYP2C9) on clinical outcomes remains unclear. Objectives We examined the association between CYP2C9/VKORC1 variants and long-term clinical outcomes in a prospective cohort study of elderly patients treated with vitamin K antagonists for venous thromboembolism (VTE). Methods We followed 774 consecutive patients aged ≥ 65 years with acute VTE from nine Swiss hospitals for a median duration of 30 months. The median duration of initial anticoagulant treatment was 9.4 months. The primary outcome was the time to any clinical event (i.e. the composite endpoint of overall mortality, major and non-major bleeding, and recurrent VTE. Results Overall, 604 (78%) patients had a CYP2C9 or VKORC1 variant. Three hundred and thirty-four patients (43.2%) had any clinical event, 119 (15.4%) died, 100 (12.9%) had major and 167 (21.6%) non-major bleeding, and 100 had (12.9%) recurrent VTE. After adjustment, CYP2C9 (but not VKORC1) variants were associated with any clinical event (hazard ratio [HR], 1.34; 95% confidence interval [CI], 1.08-1.66), death (HR, 1.74; 95% CI, 1.19-2.52) and clinically relevant non-major bleeding (sub-hazard ratio [SHR], 1.39; 95% CI, 1.02-1.89), but not with major bleeding (SHR, 1.03; 95% CI, 0.69-1.55) or recurrent VTE (SHR, 0.95; 95% CI, 0.62-1.44). Patients with genetic variants had a slightly lower anticoagulation quality. Conclusions CYP2C9 was associated with long-term overall mortality and non-major bleeding. Although genetic variants were associated with a slightly lower anticoagulation quality, there was no relationship between genetic variants and major bleeding or VTE recurrence.

Stereospecific Metabolism of R- and S-Warfarin by Human Hepatic Cytosolic Reductases

Coumadin (rac-warfarin) is the most commonly used anticoagulant in the world; however, its clinical use is often challenging because of its narrow therapeutic range and interindividual variations in response. A critical contributor to the uncertainty is variability in warfarin metabolism, which includes mostly oxidative but also reductive pathways. Reduction of each warfarin enantiomer yields two warfarin alcohol isomers, and the corresponding four alcohols retain varying levels of anticoagulant activity. Studies on the kinetics of warfarin reduction have often lacked resolution of parent-drug enantiomers and have suffered from coelution of pairs of alcohol metabolites; thus, those studies have not established the importance of individual stereospecific reductive pathways. We report the first steady-state analysis of R- and S-warfarin reduction in vitro by pooled human liver cytosol. As determined by authentic standards, the major metabolites were 9R,11S-warfarin alcohol for R-warfarin and 9S,11S-warfarin alcohol for S-warfarin. R-warfarin (Vmax 150 pmol/mg per minute, Km 0.67 mM) was reduced more efficiently than S-warfarin (Vmax 27 pmol/mg per minute, Km 1.7 mM). Based on inhibitor phenotyping, carbonyl reductase-1 dominated R-and S-warfarin reduction, followed by aldo-keto reductase-1C3 and then other members of that family. Overall, the carbonyl at position 11 undergoes stereospecific reduction by multiple enzymes to form the S alcohol for both drug enantiomers, yet R-warfarin undergoes reduction preferentially. This knowledge will aid in assessing the relative importance of reductive pathways for R- and S-warfarin and factors influencing levels of pharmacologically active parent drugs and metabolites, thus impacting patient dose responses.

Patient Decisions to Receive Secondary Pharmacogenomic Findings and Development of a Multidisciplinary Practice Model to Integrate Results Into Patient Care

Whole exome sequencing (WES) has the potential of identifying secondary findings that are predictive of poor pharmacotherapy outcomes. The purpose of this study was to investigate patients’ wishes regarding the reporting of secondary pharmacogenomic findings. WES results (n = 106 patients) were retrospectively reviewed to determine the number of patients electing to receive secondary pharmacogenomic results. Phenotypes were assigned based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. The percent of patients with a predicted phenotype associated with a gene‐based CPIC dosing recommendation was determined. Ninety‐nine patients (93.4%) elected to receive secondary pharmacogenomic findings. For each gene–drug pair analyzed, the number of patients with an actionable phenotype ranged from two (2%) to 43 patients (43.4%). Combining all gene–drug pairs, 84 unique patients (84.8%) had an actionable phenotype. A prospective multidisciplinary practice model was developed for integrating secondary pharmacogenomic findings into clinical practice. Our model highlights a unique collaboration between physician‐geneticists, pharmacists, and genetic counselors.

Warfarin genotyping with hybridization-induced aggregation on a poly(ethylene terephthalate) microdevice

A novel genotyping method is established, using allele-specific PCR followed by hybridization-induced aggregation (HIA) of microbeads on a multiplexed microdevice.