Randomized Trial of Genotype-Guided Versus Standard Warfarin Dosing in Patients Initiating Oral Anticoagulation

Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature.

Pharmacogenetic guided versus standard warfarin dosing for routine clinical care with its pharmacoeconomic impact: a randomized controlled clinical trial

BACKGROUND

Empirical use of pharmacogenetic test(PGT) is advocated for many drugs, and resource-rich setting hospitals are using the same commonly. The clinical translation of pharmacogenetic tests in terms of cost and clinical utility is yet to be examined in hospitals of low middle income countries (LMICs).

AIM

The present study assessed the clinical utility of PGT by comparing the pharmacogenetically(PGT) guided- versus standard of care(SOC)- warfarin therapy, including the health economics of the two warfarin therapies.

METHODS

An open-label, randomized, controlled clinical trial recruited warfarin-receiving patients in pharmacogenetically(PGT) guided- versus standard of care(SOC)- study arms. Pharmacogenetic analysis of CYP2C9*2(rs1799853), CYP2C9*3(rs1057910) and VKORC1(rs9923231) was performed for patients recruited to the PGT-guided arm. PT(Prothrombin Time)-INR(international normalized ratio) testing and dose titrations were allowed as per routine clinical practice. The primary endpoint was the percent time spent in the therapeutic INR range(TTR) during the 90-day observation period. Secondary endpoints were time to reach therapeutic INR(TRT), the proportion of adverse events, and economic comparison between two modes of therapy in a Markov model built for the commonest warfarin indication- atrial fibrillation.

RESULTS

The study enrolled 168 patients, 84 in each arm. Per-protocol analysis showed a significantly high median time spent in therapeutic INR in the genotype-guided arm(42.85%; CI 21.4-66.75) as compared to the SOC arm(8.8%; CI 0-27.2)(p < 0.00001). The TRT was less in the PG-guided warfarin dosing group than the standard-of-care dosing warfarin group (17.85 vs. 33.92 days) (p = 0.002). Bleeding and thromboembolic events were similar in the two study groups. Lifetime expenditure was ₹1,26,830 in the PGT arm compared to ₹1,17,907 in the SOC arm. The QALY gain did not differ in the two groups(3.9 vs. 3.65). Compared to SOC, the incremental cost-utility ratio was ₹35,962 per QALY gain with PGT test opting. In deterministic and probabilistic sensitivity analysis, the base case results were found to be insensitive to the variation in model parameters. In the cost-effectiveness-acceptability curve analysis, a 90% probability of cost-effectiveness was reached at a willingness-to-pay(WTP) of ₹ 71,630 well below one time GDP threshold of WTP used.

CONCLUSION

Clinical efficacy and the cost-effectiveness of the warfarin pharmacogenetic test suggest its routine use as a point of care investigation for patient care in LMICs.

Warfarin-A natural anticoagulant: A review of research trends for precision medication

BACKGROUND

Warfarin is a widely prescribed anticoagulant in the clinic. It has a more considerable individual variability, and many factors affect its variability. Mathematical models can quantify the quantitative impact of these factors on individual variability.

PURPOSE

The aim is to comprehensively analyze the advanced warfarin dosing algorithm based on pharmacometrics and machine learning models of personalized warfarin dosage.

METHODS

A bibliometric analysis of the literature retrieved from PubMed and Scopus was performed using VOSviewer. The relevant literature that reported the precise dosage of warfarin calculation was retrieved from the database. The multiple linear regression (MLR) algorithm was excluded because a recent systematic review that mainly reviewed this algorithm has been reported. The following terms of quantitative systems pharmacology, mechanistic model, physiologically based pharmacokinetic model, artificial intelligence, machine learning, pharmacokinetic, pharmacodynamic, pharmacokinetics, pharmacodynamics, and warfarin were added as MeSH Terms or appearing in Title/Abstract into query box of PubMed, then humans and English as filter were added to retrieve the literature.

RESULTS

Bibliometric analysis revealed important co-occuring MeShH and index keywords. Further, the United States, China, and the United Kingdom were among the top countries contributing in this domain. Some studies have established personalized warfarin dosage models using pharmacometrics and machine learning-based algorithms. There were 54 related studies, including 14 pharmacometric models, 31 artificial intelligence models, and 9 model evaluations. Each model has its advantages and disadvantages. The pharmacometric model contains biological or pharmacological mechanisms in structure. The process of pharmacometric model development is very time- and labor-intensive. Machine learning is a purely data-driven approach; its parameters are more mathematical and have less biological interpretation. However, it is faster, more efficient, and less time-consuming. Most published models of machine learning algorithms were established based on cross-sectional data sourced from the database.

CONCLUSION

Future research on personalized warfarin medication should focus on combining the advantages of machine learning and pharmacometrics algorithms to establish a more robust warfarin dosage algorithm. Randomized controlled trials should be performed to evaluate the established algorithm of warfarin dosage. Moreover, a more user-friendly and accessible warfarin precision medicine platform should be developed.

Atrial Fibrillation and Reperfusion Therapy in Acute Ischaemic Stroke Patients: Prevalence and Outcomes-A Comprehensive Systematic Review and Meta-Analysis

Atrial fibrillation (AF) significantly contributes to acute ischaemic stroke (AIS), yet its precise influence on clinical outcomes post-intravenous thrombolysis (IVT) and post-endovascular thrombectomy (EVT) has remained elusive. Furthermore, the overall prevalence of AF in AIS patients undergoing reperfusion therapy has not been clearly determined. Employing random-effects meta-analyses, this research aimed to estimate the pooled prevalence of AF among AIS patients undergoing reperfusion therapy, while also examining the association between AF and clinical outcomes such as functional outcomes, symptomatic intracerebral haemorrhage (sICH) and mortality. Studies comparing AF and non-AF patient groups undergoing reperfusion therapy were identified and included following an extensive database search. Forty-nine studies (n = 66,887) were included. Among IVT patients, the prevalence of AF was 31% (Effect Size [ES] 0.31 [95%CI 0.28-0.35], p < 0.01), while in EVT patients, it reached 42% (ES 0.42 [95%CI 0.38-0.46], p < 0.01), and in bridging therapy (BT) patients, it stood at 36% (ES 0.36 [95%CI 0.28-0.43], p < 0.01). AF was associated with significantly lower odds of favourable 90-day functional outcomes post IVT (Odds Ratio [OR] 0.512 [95%CI 0.376-0.696], p < 0.001), but not post EVT (OR 0.826 [95%CI 0.651-1.049], p = 0.117). Our comprehensive meta-analysis highlights the varying prevalence of AF among different reperfusion therapies and its differential impact on patient outcomes. The highest pooled prevalence of AF was observed in EVT patients, followed by BT and IVT patients. Interestingly, our analysis revealed that AF was significantly associated with poorer clinical outcomes following IVT. Such an association was not observed following EVT.

Approximating Functions with Approximate Privacy for Applications in Signal Estimation and Learning

Large corporations, government entities and institutions such as hospitals and census bureaus routinely collect our personal and sensitive information for providing services. A key technological challenge is designing algorithms for these services that provide useful results, while simultaneously maintaining the privacy of the individuals whose data are being shared. Differential privacy (DP) is a cryptographically motivated and mathematically rigorous approach for addressing this challenge. Under DP, a randomized algorithm provides privacy guarantees by approximating the desired functionality, leading to a privacy-utility trade-off. Strong (pure DP) privacy guarantees are often costly in terms of utility. Motivated by the need for a more efficient mechanism with better privacy-utility trade-off, we propose Gaussian FM, an improvement to the functional mechanism (FM) that offers higher utility at the expense of a weakened (approximate) DP guarantee. We analytically show that the proposed Gaussian FM algorithm can offer orders of magnitude smaller noise compared to the existing FM algorithms. We further extend our Gaussian FM algorithm to decentralized-data settings by incorporating the CAPE protocol and propose capeFM. Our method can offer the same level of utility as its centralized counterparts for a range of parameter choices. We empirically show that our proposed algorithms outperform existing state-of-the-art approaches on synthetic and real datasets.

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.

Optimizing the dynamic treatment regime of in-hospital warfarin anticoagulation in patients after surgical valve replacement using reinforcement learning

OBJECTIVE

Warfarin anticoagulation management requires sequential decision-making to adjust dosages based on patients' evolving states continuously. We aimed to leverage reinforcement learning (RL) to optimize the dynamic in-hospital warfarin dosing in patients after surgical valve replacement (SVR).

MATERIALS AND METHODS

10 408 SVR cases with warfarin dosage-response data were retrospectively collected to develop and test an RL algorithm that can continuously recommend daily warfarin doses based on patients' evolving multidimensional states. The RL algorithm was compared with clinicians' actual practice and other machine learning and clinical decision rule-based algorithms. The primary outcome was the ratio of patients without in-hospital INRs >3.0 and the INR at discharge within the target range (1.8-2.5) (excellent responders). The secondary outcomes were the safety responder ratio (no INRs >3.0) and the target responder ratio (the discharge INR within 1.8-2.5).

RESULTS

In the test set (n = 1260), the excellent responder ratio under clinicians' guidance was significantly lower than the RL algorithm: 41.6% versus 80.8% (relative risk [RR], 0.51; 95% confidence interval [CI], 0.48-0.55), also the safety responder ratio: 83.1% versus 99.5% (RR, 0.83; 95% CI, 0.81-0.86), and the target responder ratio: 49.7% versus 81.1% (RR, 0.61; 95% CI, 0.58-0.65). The RL algorithms performed significantly better than all the other algorithms. Compared with clinicians' actual practice, the RL-optimized INR trajectory reached and maintained within the target range significantly faster and longer.

DISCUSSION

RL could offer interactive, practical clinical decision support for sequential decision-making tasks and is potentially adaptable for varied clinical scenarios. Prospective validation is needed.

CONCLUSION

An RL algorithm significantly optimized the post-operation warfarin anticoagulation quality compared with clinicians' actual practice, suggesting its potential for challenging sequential decision-making tasks.

Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis

We constructed a cost-effectiveness model to assess the clinical and economic value of a CDS alert program that provides pharmacogenomic (PGx) testing results, compared to no alert program in acute coronary syndrome (ACS) and atrial fibrillation (AF), from a health system perspective. We defaulted that 20% of 500,000 health-system members between the ages of 55 and 65 received PGx testing for CYP2C19 (ACS-clopidogrel) and CYP2C9, CYP4F2 and VKORC1 (AF-warfarin) annually. Clinical events, costs, and quality-adjusted life years (QALYs) were calculated over 20 years with an annual discount rate of 3%. In total, 3169 alerts would be fired. The CDS alert program would help avoid 16 major clinical events and 6 deaths for ACS; and 2 clinical events and 0.9 deaths for AF. The incremental cost-effectiveness ratio was $39,477/QALY. A PGx-CDS alert program was cost-effective, under a willingness-to-pay threshold of $100,000/QALY gained, compared to no alert program.

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.

Genetic-Guided Pharmacotherapy for Atrial Fibrillation: A Systematic and Critical Review of Economic Evaluations

OBJECTIVES

This study aimed to examine the extent and quality of evidence from economic evaluations (EEs) of genetic-guided pharmacotherapy (PGx) for atrial fibrillation (AF) and to identify variables influential in changing base-case conclusions.

METHODS

From systematic searches, we included EEs of existing PGx testing to guide pharmacotherapy for AF, without restrictions on population characteristics or language. Articles excluded were genetic tests used to guide device-based therapy or focused on animals.

RESULTS

We found 18 EEs (46 comparisons), all model-based cost-utility analysis with or without cost-effectiveness analysis mostly from health system's perspectives, of PGx testing to determine coumadin/direct-acting anticoagulant (DOAC) dosing (14 of 18), to stratify patients into coumadin/DOACs (3 of 18), or to increase patients' adherence to coumadin (1 of 18) versus non-PGx. Most PGx to determine coumadin dosing found PGx more costly and more effective than standard or clinical coumadin dosing (19 of 24 comparisons) but less costly and less effective than standard DOAC dosing (14 of 14 comparisons). The remaining comparisons were too few to observe any trend. Of 61 variables influential in changing base-case conclusions, effectiveness of PGx testing was the most common (37%), accounted for in the models using time-based or medication-based approaches or relative risk. The cost of PGx testing has decreased and plateaued over time.

CONCLUSIONS

EEs to date only partially inform decisions on selecting optimal PGx testing for AF, because most evidence focuses on PGx testing to determine coumadin dosing, but less on other purposes. Future EE may refer to the list of influential variables and the approaches used to account for the effect of PGx testing to inform data collection and study design.

Changing from mandatory to optional genotyping results in higher acceptance of pharmacist-guided warfarin dosing

Aim: We evaluated the clinical acceptance and feasibility of a pharmacist-guided personalized consult service following its transition from a mandatory (mPGx) to optional (oPGx) CYP2C9/VKORC1/CYP4F2 genotyping for warfarin. Methods: A total of 1105 patients were included. Clinical acceptance and feasibility outcomes were analyzed using bivariate and multivariable analyses. Results: After transitioning to optional genotyping, genotype testing was still ordered in a large segment of the eligible population (52.1%). Physician acceptance of pharmacist-recommended doses improved from 83.9% (mPGx) to 86.6% (oPGx; OR: 1.3; 95% CI: 1.1-1.5; p = 0.01) with a shorter median genotype result turnaround time (oPGX: 23.6 h vs mPGX: 25.1 h; p < 0.01). Conclusion: Ordering of genotype testing and provider acceptance of dosing recommendations remained high after transitioning to optional genotyping.

Efficacy and safety of genotype-guided warfarin dosing versus non-genotype-guided warfarin dosing strategies: A systematic review and meta-analysis of 27 randomized controlled trials

OBJECTIVE

To evaluate the efficacy and safety of genotype-guided dosing (GD) strategies compared to non-genotype-guided dosing (non-GD) strategies for warfarin.

METHODS

Databases were searched up to July 2021. Meta-analysis was conducted with the Review Manager software (version 5.4) and R (version 4.0.5). Risk ratio (RR), mean difference (MD), and 95% confidence intervals (CIs) were used. Subgroup analyses were conducted based on ethnicity and dosing regimen in non-GD group. Meta-regression was performed to evaluate the relation of covariates. This study is registered with PROSPERO (CRD42021245654).

RESULTS

27 randomized controlled trials with a total of 9906 patients were included. The GD group resulted in a significantly improved time in therapeutic range compared with non-GD group in follow-up duration within 30 days (MD: 5.95, 95%CI: 2.41-9.22, P = 0.001) and beyond 30 days (MD: 4.93, 1.40-8.47, P = 0.006), time to the first therapeutic international normalized ratio (MD: -1.80, -2.69 - -0.92, P < 0.0001), and time to reach stable dose (MD: -5.08, -7.09 - -3.07, P < 0.00001), incidence of major bleeding events (RR: 0.50, 0.33-0.75, P = 0.0008), total bleeding events (RR: 0.83, 0.73-0.95, P = 0.006), and thromboembolism (RR: 0.69, 0.49-0.96, P = 0.03). No differences were found in stable dose achievement, minor bleeding events, over anticoagulation, and all-cause mortality. Four improved efficacy outcomes were observed in GD group compared with fixed dosing group. Only time to the therapeutic INR was shortened in GD group compared with clinical adjusted dosing group. The result showed no difference of safety outcomes between GD group and fixed dosing group whereas a decreased incidence of major bleeding events was observed when comparing to clinical adjusted dosing group.

CONCLUSION

GD strategy was superior to fixed dosing strategy in term of efficacy outcomes and comparable to fixed dosing strategy in safety outcomes. Clinical adjusted regimen could partly substitute the genotype-guided dosing strategy for efficacy in insufficient conditions, but the risk of major bleeding events should be monitored.

Pharmacogenetic testing for adverse drug reaction prevention: systematic review of economic evaluations and the appraisal of quality matters for clinical practice and implementation

Background

Genetic testing has potential roles in identifying whether an individual would have risk of adverse drug reactions (ADRs) from a particular medicine. Robust cost-effectiveness results on genetic testing would be useful for clinical practice and policy decision-making on allocating resources effectively. This study aimed to update a systematic review on economic evaluations of pharmacogenetic testing to prevent ADRs and critically appraise the quality of reporting and sources of evidence for model input parameters.

Methods

We searched studies through Medline via PubMed, Scopus and CRD’s NHS Economic Evaluation up to October 2019. Studies investigating polymorphism-based pharmacogenetic testing, which guided drug therapies to prevent ADRs, using economic evaluation methods were included. Two reviewers independently performed data extraction and assessed the quality of reporting using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines and the quality of data sources using the hierarchy of evidence developed by Cooper et al.

Results

Fifty-nine economic evaluations of pharmacogenetic testing to avoid drug-induced ADRs were found between 2002 and 2018. Cost-utility and cost-effectiveness analyses were the most common methods of economic evaluation of pharmacogenetic testing. Most studies complied with the CHEERS checklist, except for single study-based economic evaluations which did not report uncertainty analysis (78%). There was a lack of high-quality evidence not only for estimating the clinical effectiveness of pharmacogenetic testing, but also baseline clinical data. About 14% of the studies obtained clinical effectiveness data of testing from a meta-analysis of case-control studies with direct comparison, which was not listed in the hierarchy of evidence used.

Conclusions

Our review suggested that future single study-based economic evaluations of pharmacogenetic testing should report uncertainty analysis, as this could significantly affect the robustness of economic evaluation results. A specific ranking system for the quality of evidence is needed for the economic evaluation of pharmacogenetic testing of ADRs. Differences in parameters, methods and outcomes across studies, as well as population-level and system-level differences, may lead to the difficulty of comparing cost-effectiveness results across countries.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07025-8.

Eighty years of oral anticoagulation: Learning from history

In the year 2021 we celebrate the 80th anniversary of the first clinical use of vitamin K antagonists (VKAs), the mainstay of prevention and long-term treatment of thromboembolic disease. The discovery and development of oral anticoagulants is one of the most important chapters in the history of medicine, a goal pursued by physicians trying to combat the clinical manifestations of thrombosis since ancient times. Until the last decade, VKAs were the only oral anticoagulants available and used in clinical practice. Today, their clinical use has progressively shrunk, as the non-vitamin K antagonist oral anticoagulants (NOACs) are increasingly replacing VKAs in various conditions after the successful completion of several large randomized controlled trials. Currently, new research is tackling upstream components of the intrinsic pathway - particularly factor XI and factor XII - for the development of new, even safer anticoagulants promising to reduce bleeding without compromising efficacy. This review highlights the evolution of oral anticoagulant therapy tracing the key stages of a long and fascinating history that has unfolded from the first part of the twentieth century until today, indeed an intriguing journey where serendipity is intertwined with the tenacious work of many researchers.

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.

Warfarin maintenance dose prediction for Chinese after heart valve replacement by a feedforward neural network with equal stratified sampling

Patients requiring low-dose warfarin are more likely to suffer bleeding due to overdose. The goal of this work is to improve the feedforward neural network model's precision in predicting the low maintenance dose for Chinese in the aspect of training data construction. We built the model from a resampled dataset created by equal stratified sampling (maintaining the same sample number in three dose-groups with a total of 3639) and performed internal and external validations. Comparing to the model trained from the raw dataset of 19,060 eligible cases, we improved the low-dose group's ideal prediction percentage from 0.7 to 9.6% and maintained the overall performance (76.4% vs. 75.6%) in external validation. We further built neural network models on single-dose subsets to invest whether the subsets samples were sufficient and whether the selected factors were appropriate. The training set sizes were 1340 and 1478 for the low and high dose subsets; the corresponding ideal prediction percentages were 70.2% and 75.1%. The training set size for the intermediate dose varied and was 1553, 6214, and 12,429; the corresponding ideal prediction percentages were 95.6, 95.1%, and 95.3%. Our conclusion is that equal stratified sampling can be a considerable alternative approach in training data construction to build drug dosing models in the clinic.

Acenocoumarol Pharmacogenetic Dosing Algorithm versus Usual Care in Patients with Venous Thromboembolism: A Randomised Clinical Trial

Patients with venous thromboembolism (VTE) require immediate treatment with anticoagulants such as acenocoumarol. This multicentre randomised clinical trial evaluated the effectiveness of a dosing pharmacogenetic algorithm versus a standard-of-care dose adjustment at the beginning of acenocoumarol treatment. We included 144 patients with VTE. On the day of recruitment, a blood sample was obtained for genotyping (CYP2C9*2, CYP2C9*3, VKORC1, CYP4F2, APOE). Dose adjustment was performed on day 3 or 4 after the start of treatment according to the assigned group and the follow-up was at 12 weeks. The principal variable was the percentage of patients with an international normalised ratio (INR) within the therapeutic range on day 7. Thirty-four (47.2%) patients had an INR within the therapeutic range at day 7 after the start of treatment in the genotype-guided group compared with 14 (21.9%) in the control group (p = 0.0023). There were no significant differences in the time to achieve a stable INR, the number of INRs within the range in the first 6 weeks and at the end of study. Our results suggest the use of a pharmacogenetic algorithm for patients with VTE could be useful in achieving target INR control in the first days of treatment.

Current challenges and opportunities for pharmacogenomics: perspective of the Industry Pharmacogenomics Working Group (I-PWG)

Pharmaceutical companies have increasingly utilized genomic data for the selection of drug targets and the development of precision medicine approaches. Most major pharmaceutical companies routinely collect DNA from clinical trial participants and conduct pharmacogenomic (PGx) studies. However, the implementation of PGx studies during clinical development presents a number of challenges. These challenges include adapting to a constantly changing global regulatory environment, challenges in study design and clinical implementation, and the increasing concerns over patient privacy. Advances in the field of genomics are also providing new opportunities for pharmaceutical companies, including the availability of large genomic databases linked to patient health information, the growing use of polygenic risk scores, and the direct sequencing of clinical trial participants. The Industry Pharmacogenomics Working Group (I-PWG) is an association of pharmaceutical companies actively working in the field of pharmacogenomics. This I-PWG perspective will provide an overview of the steps pharmaceutical companies are taking to address each of these challenges, and the approaches being taken to capitalize on emerging scientific opportunities.

Establishment of predicting equation for individual sufentanil dosage postoperatively based on gene polymorphisms

BACKGROUND

Postoperative analgesia is widely used for patients undergoing major surgeries. Individual differences in genetic polymorphisms may be obstructive factors for accurately anesthetics using. However, the equation for predicting sufentanil dosage postoperatively based on genetic design has been established yet. Our aim was to establish sufentanil dosage postoperatively prediction equation based on patients' genetic polymorphisms.

METHODS

One hundred forty patients with total gastrectomy and radical resection of pulmonary carcinoma were included. To establish sufentanil dosage postoperatively for patients with gastric cancer, we collected patients' basic information and CYP3A4*1G, COMTVal158Met, OPRM1A118G, and ABCB1C3435T gene sequencing results. To verify this equation, we put patients' with lung cancer surgeries information into it.

RESULTS

The sufentanil dosage prediction equation postoperatively was y = 4.104 - 0.222 × (gender) + 0.021 × (OPRM1A118G) + 0.249 × (ABCB1C3435T). Patients' with lung cancer surgeries information were substituted into it. The results showed no significant differences between predicted and actual sufentanil dosage (p > 0.05).

CONCLUSION

We established the prediction equation for individual sufentanil dosage postoperatively based on gene polymorphisms. The results showed this prediction equation was valid, which might be used for different types of surgeries. We established an equation for individual dosage of sufentanil for postoperative analgesia based on gene polymorphisms. The results show that the prediction equation is valid, the information might be used for different types of postoperative analgesia, and the painful patients will have great potential safe and personalized pain control after analgesic therapy. It might also have potential as a clinical tool.

An Adapted Neural-Fuzzy Inference System Model Using Preprocessed Balance Data to Improve the Predictive Accuracy of Warfarin Maintenance Dosing in Patients After Heart Valve Replacement

BACKGROUND

Tailoring warfarin use poses a challenge for physicians and pharmacists due to its narrow therapeutic window and substantial inter-individual variability. This study aimed to create an adapted neural-fuzzy inference system (ANFIS) model using preprocessed balance data to improve the predictive accuracy of warfarin maintenance dosing in Chinese patients undergoing heart valve replacement (HVR).

METHODS

This retrospective study enrolled patients who underwent HVR between June 1, 2012, and June 1, 2016, from 35 centers in China. The primary outcomes were the mean difference between predicted warfarin dose by ANFIS models and actual dose and the models' predictive accuracy, including the ideal predicted percentage, the mean absolute error (MAE), and the mean squared error (MSE). The eligible cases were divided into training, internal validation, and external validation groups. We explored input variables by univariate analysis of a general linear model and created two ANFIS models using imbalanced and balanced training sets. We finally compared the primary outcomes between the imbalanced and balanced ANFIS models in both internal and external validation sets. Stratified analyses were conducted across warfarin doses (low, medium, and high doses).

RESULTS

A total of 15,108 patients were included and grouped as follows: 12,086 in the imbalanced training set; 2820 in the balanced training set; 1511 in the internal validation set; and 1511 in the external validation set. Eight variables were explored as predictors related to warfarin maintenance doses, and imbalanced and balanced ANFIS models with multi-fuzzy rules were developed. The results showed a low mean difference between predicted and actual doses (< 0.3 mg/d for each model) and an accurate prediction property in both the imbalanced model (ideal prediction percentage, 74.39-78.16%; MAE, 0.37 mg/daily; MSE, 0.39 mg/daily) and the balanced model (ideal prediction percentage, 73.46-75.31%; MAE, 0.42 mg/daily; MSE, 0.43 mg/daily). Compared to the imbalanced model, the balanced model had a significantly higher prediction accuracy in the low-dose (14.46% vs. 3.01%; P < 0.001) and the high-dose warfarin groups (34.71% vs. 23.14%; P = 0.047). The results from the external validation cohort confirmed this finding.

CONCLUSIONS

The ANFIS model can accurately predict the warfarin maintenance dose in patients after HVR. Through data preprocessing, the balanced model contributed to improved prediction ability in the low- and high-dose warfarin groups.

Ischemic Stroke Risk Factors in Patients with Atrial Fibrillation Treated with New Oral Anticoagulants

The most commonly used therapeutic option for the prevention of ischemic stroke in patients with atrial fibrillation is new- or old-generation oral anticoagulants. New oral anticoagulants are at least as effective as old-generation oral anticoagulants in the prevention of ischemic stroke, with a reduced risk of life-threatening hemorrhage. Moreover, the constant monitoring of these drugs in the patient’s blood is not required during routine use. However, ischemic stroke can still occur in these patients. Therefore, the aim of this study was to investigate the pattern of risk factors for ischemic stroke in patients with atrial fibrillation treated with new oral anticoagulants. Our multicenter retrospective study involved 2032 patients with acute ischemic stroke. The experimental group consisted of 256 patients with acute ischemic stroke and nonvalvular atrial fibrillation, who were treated with new oral anticoagulants. The control group consisted of 1776 ischemic stroke patients without coexisting atrial fibrillation. The results of our study show that patients with atrial fibrillation treated with new oral anticoagulants are more likely to display thrombotic, proatherogenic, and proinflammatory factors in addition to the embolic factors associated with atrial fibrillation. Therefore, solely taking new oral anticoagulants is insufficient in protecting this group of patients from ischemic stroke.

Pharmacogenetic algorithm for predicting daily dose of warfarin in Caucasian patients of Czech origin

OBJECTIVES

Warfarin use is limited by a low therapeutic index and significant interindividual variability of the daily dose. The most important factor predicting daily warfarin dose is individual genotype, polymorphisms of genes CYP2C9 (warfarin metabolism) and VKORC1 (sensitivity for warfarin). Algorithms using clinical and genetic variables could predict the daily dose before the initiation of therapy. The aim of this study was to develop and validate an algorithm for the prediction of warfarin daily dose in Czech patients.

METHODS

Detailed clinical data of patients with known and stable warfarin daily dose were collected. All patients were genotyped for polymorphisms in genes CYP2C9 and VKORC1.

RESULTS

Included patients were divided into derivation (n=175) and validation (n=223) cohorts. The final algorithm includes the following variables: Age, height, weight, treatment with amiodarone and presence of variant alleles of genes CYP2C9 and VKORC1. The adjusted coefficient of determination is 72.4% in the derivation and 62.3% in the validation cohort (p<0.001).

CONCLUSIONS

Our validated algorithm for warfarin daily dose prediction in our Czech cohort had higher precision than other currently published algorithms. Pharmacogenetics of warfarin has the potential in the clinical practice in specialized centers.

A network meta-analysis of CYP2C9, CYP2C9 with VKORC1 and CYP2C9 with VKORC1 and CYP4F2 genotype-based warfarin dosing strategies compared to traditional

WHAT IS KNOWN AND OBJECTIVES

Variations in genotypes were observed in randomized clinical trials (RCTs) that evaluated genotype-based warfarin dosing. We carried out a network meta-analysis to assess whether any clinically significant differences exist between RCTs evaluating CYP2C9 with VKORC1, with CYP2C9 alone and CYP2C9, VKORC1, with CYP4F2 dosing strategies.

METHODS

Electronic records were searched for RCTs comparing genotype-based warfarin with traditional-dosing strategies. Key outcomes included were the time to first therapeutic international normalized ratio (INR); time to stable INR or warfarin dose; percent time in therapeutic range (TTR); and the proportion of patients with supra-therapeutic INR. Weighted mean differences (WMD) and odds ratios (OR) with 95% confidence intervals (95% CI) were the effect estimates.

RESULTS AND DISCUSSION

Twenty-six studies (7898 patients) were included. CYP2C9-based warfarin dosing was associated with a shorter time to first therapeutic INR (WMD: -2.73, 95% CI: -3.41, -2.05) and stable INR/warfarin dose (WMD: -8.1, 95% CI: -12.54, -3.66). CYP2C9 and VKORC1 were observed with a shorter time to first therapeutic INR (WMD: -1.92, 95% CI: -3.23, -0.61) and stable INR/warfarin dose (WMD: -4.6, 95% CI: -6.87, -2.34) along with a longer TTR (%) (WMD: 3.91, 95% CI: 1.18, 6.63). CYP2C9, VKORC1 and CYP4F2 were observed with a reduced proportion of patients with supra-therapeutic INR (OR: 0.68, 95% CI: 0.49, 0.93). Trial sequential analysis confirms the superior benefits of CYP2C9 with VKORC1 genotype.

WHAT IS NEW AND CONCLUSION

The present evidence is supportive of personalizing warfarin dose based only on CYP2C9 and VKORC1 genotypes compared to traditional strategies. More RCTs are needed to delineate any benefit for adding CYP4F2 to provide sufficient power for pooled analysis. No convincing evidence exists supporting the role of CYP2C9 alone.

Precision Medicine, AI, and the Future of Personalized Health Care

The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less‐common responses to treatment or unique healthcare needs. AI leverages sophisticated computation and inference to generate insights, enables the system to reason and learn, and empowers clinician decision making through augmented intelligence. Recent literature suggests that translational research exploring this convergence will help solve the most difficult challenges facing precision medicine, especially those in which nongenomic and genomic determinants, combined with information from patient symptoms, clinical history, and lifestyles, will facilitate personalized diagnosis and prognostication.

Analysis of biomarkers and metabolic pathways in patients with unstable angina based on ultra‑high‑performance liquid chromatography‑quadrupole time‑of‑flight mass spectrometry

Unstable angina (UA) is a coronary disease with a high mortality and morbidity worldwide. The present study aimed to use non-invasive techniques to identify urine biomarkers in patients with UA, so as to provide more information for the early diagnosis and treatment of the disease. Based on metabolomics, urine samples from 28 patients with UA and 28 healthy controls (HCs) were analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). A total of 16 significant biomarkers that could distinguish between patients with UA and HCs, including D-glucuronic acid, creatinine, succinic acid and N-acetylneuraminic acid, were identified. The major metabolic pathways associated with UA were subsequently analyzed by non-targeted metabolomics. The results demonstrated that amino acid and energy metabolism, fatty acid metabolism, purine metabolism and steroid hormone biosynthetic metabolism may serve important roles in UA. The results of the current study may provide a theoretical basis for the early diagnosis of UA and novel treatment strategies for clinicians. The trial was registered with the Chinese Clinical Trial Registration Center (registration no. ChiCTR-ROC-17013957) at Tianjin University of Traditional Chinese Medicine.

Real-Life International Normalized Ratio Profile in Patients with Non-Valvular Atrial Fibrillation Prescribed Vitamin K Antagonist

Coagulation status with vitamin K antagonists (VKAs) needs to be monitored carefully to ensure maximal efficacy with minimal complication rates.

Aim. To study the international normalized ratio (INR) values in patients on VKAs in selected area, find out which patient characteristics that is associated with good INR control and calculation of the time in the therapeutic range (TTR) according to the number of INR/Patient.

Material and methods. A total of 200 patients with non-valvular atrial fibrillation prescribed vitamin K antagonist as anticoagulant were evaluated. They were divided into two groups: group I with TTR≥65% (n=93) and group II with TTR<65% (n=107). Stroke and hemorrhagic risks were calculated by means of the CHA2DS2-VASc score and HAS-BLED score, respectively. Presence of comorbid diseases was assessed by the Charlson index. TTR was calculated using Rosendaal method.

Results. Patients in group I (TTR≥65%) were younger (p<0.001), more often men (p<0.074) with a high level of education (p<0.001), had lower stroke and hemorrhagic risks (mean CHA2DS2-VASc score was 1.0 and HAS-BLED score – 0.0), and also had fewer comorbidities (mean Charlson index was 0.0; p<0.001) compared to patients in group II (TTR<65%). The rate of inadequate control with VKAs (TTR<65) was 52%. Multivariate logistic regression analysis was done to see the significant independent predictors for a good INR control i.e. TTR≥65%. It was found that high level of education compared to lower levels is the only significant independent predictor for obtaining good INR control (odds ratio=133, 95% confidence interval 34.24-514.44, p<0.001).

Conclusion. It was found that high level of education compared to lower levels is the only significant independent predictor for obtaining good INR control.

Genotype-Guided Dosing of Warfarin in Chinese Adults: A Multicenter Randomized Clinical Trial

BACKGROUND

Warfarin is an effective treatment for thromboembolic disease but has a narrow therapeutic index; optimal anticoagulation dosage can differ tremendously among individuals. We aimed to evaluate whether genotype-guided warfarin dosing is superior to routine clinical dosing for the outcomes of interest in Chinese patients.

METHODS

We conducted a multicenter, randomized, single-blind, parallel-controlled trial from September 2014 to April 2017 in 15 hospitals in China. Eligible patients were ≥18 years of age, with atrial fibrillation or deep vein thrombosis without previous treatment of warfarin or a bleeding disorder. Nine follow-up visits were performed during the 12-week study period. The primary outcome measure was the percentage of time in the therapeutic range of the international normalized ratio during the first 12 weeks after starting warfarin therapy.

RESULTS

A total of 660 participants were enrolled and randomly assigned to a genotype-guided dosing group or a control group under standard dosing. The genotype-guided dosing group had a significantly higher percentage of time in the therapeutic range than the control group (58.8% versus 53.2% [95% CI of group difference, 1.1-10.2]; P=0.01). The genotype-guided dosing group also achieved the target international normalized ratio sooner than the control group. In subgroup analyses, warfarin normal sensitivity group had an even higher percentage of time in the therapeutic range during the first 12 weeks compared with the control group (60.8% versus 48.9% [95% CI, 1.1-24.4]). The incidence of adverse events was low in both groups.

CONCLUSIONS

The outcomes of genotype-guided warfarin dosing were superior to those of clinical standard dosing. These findings raise the prospect of precision warfarin treatment in China. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02211326.

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.

The Implementation Chasm Hindering Genome-informed Health Care

The promises of precision medicine are often heralded in the medical and lay literature, but routine integration of genomics in clinical practice is still limited. While the "last mile' infrastructure to bring genomics to the bedside has been demonstrated in some healthcare settings, a number of challenges remain - both in the receptivity of today's health system and in its technical and educational readiness to respond to this evolution in care. To improve the impact of genomics on health and disease management, we will need to integrate both new knowledge and new care processes into existing workflows. This change will be onerous and time-consuming, but hopefully valuable to the provision of high quality, economically feasible care worldwide.

Ischemic Stroke despite Oral Anticoagulant Therapy in Patients with Atrial Fibrillation

OBJECTIVE

It is not known whether patients with atrial fibrillation (AF) with ischemic stroke despite oral anticoagulant therapy are at increased risk for further recurrent strokes or how ongoing secondary prevention should be managed.

METHODS

We conducted an individual patient data pooled analysis of 7 prospective cohort studies that recruited patients with AF and recent cerebral ischemia. We compared patients taking oral anticoagulants (vitamin K antagonists [VKA] or direct oral anticoagulants [DOAC]) prior to index event (OACprior ) with those without prior oral anticoagulation (OACnaive ). We further compared those who changed the type (ie, from VKA or DOAC, vice versa, or DOAC to DOAC) of anticoagulation (OACchanged ) with those who continued the same anticoagulation as secondary prevention (OACunchanged ). Time to recurrent acute ischemic stroke (AIS) was analyzed using multivariate competing risk Fine-Gray models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

We included 5,413 patients (median age = 78 years [interquartile range (IQR) = 71-84 years]; 5,136 [96.7%] had ischemic stroke as the index event, median National Institutes of Health Stroke Scale on admission = 6 [IQR = 2-12]). The median CHA2 DS2 -Vasc score (congestive heart failure, hypertension, age≥ 75 years, diabetes mellitus, stroke/transient ischemic attack, vascular disease, age 65-74 years, sex category) was 5 (IQR = 4-6) and was similar for OACprior (n = 1,195) and OACnaive (n = 4,119, p = 0.103). During 6,128 patient-years of follow-up, 289 patients had AIS (4.7% per year, 95% CI = 4.2-5.3%). OACprior was associated with an increased risk of AIS (HR = 1.6, 95% CI = 1.2-2.3, p = 0.005). OACchanged (n = 307) was not associated with decreased risk of AIS (HR = 1.2, 95% CI = 0.7-2.1, p = 0.415) compared with OACunchanged (n = 585).

INTERPRETATION

Patients with AF who have an ischemic stroke despite previous oral anticoagulation are at a higher risk for recurrent ischemic stroke despite a CHA2 DS2 -Vasc score similar to those without prior oral anticoagulation. Better prevention strategies are needed for this high-risk patient group. ANN NEUROL 2020.

Metabolomics and its application in the treatment of coronary heart disease with traditional Chinese medicine

Traditional Chinese Medicine (TCM) is the treasure of Chinese Nation and gained the gradual acceptance of the international community. However, the methods and theories of TCM understanding of diseases are lack of appropriate modern scientific characterization systems. Moreover, traditional risk factors cannot promote to detection and prevent those patients with coronary artery disease (CAD) who have not developed acute myocardial infarction (MI) in time. To sum up, there is still no objective systematic evaluation system for the therapeutic mechanism of TCM in the prevention and cure of cardiovascular disease. Thus, new ideas and technologies are needed. The development of omics technology, especially metabolomics, can be used to predict the level of metabolites in vivo and diagnose the physiological state of the body in time to guide the corresponding intervention. In particular, metabolomics is also a very powerful tool to promote the modernization of TCM and the development of TCM in personalized medicine. This article summarized the application of metabolomics in the early diagnosis, the discovery of biomarkers and the treatment of TCM in CAD.

A Simple Formula for Predicting the Maintenance Dose of Warfarin with Reference to the Initial Response to Low Dosing at an Outpatient Clinic

Objective The pharmacodynamic effect of warfarin varies among individuals, and its maintenance dose is widely distributed. Although many formulae for predicting the maintenance dose of warfarin have been developed, most of them are complex and not in practical use. Methods and Materials Among 12,738 new patients visiting the Cardiovascular Institute between 2004 and 2009, we identified 127 patients (66.6±8.8 years, 89 men) with atrial fibrillation for whom warfarin was newly started with an initial dose of 2 mg/day and the international normalized ratio (INR) at 1 year after warfarin was started was within the therapeutic range. The prediction models for the maintenance dose were developed by an exponential equation and a first-order equation. Results The initial response of the INR to the dose of 2 mg/day (initial INR) ranged from 1.00-3.24 (mean 1.43), while the maintenance dose of warfarin ranged from 0.5-14 mg (mean 3.8 mg). The maintenance dose showed an exponential correlation to the initial INR: (predicted maintenance dose) =5.522× (initial INR) ^-1.556 (R²=0.795, p<0.001). Excluding the patients with a poor response to the initial dose (initial INR <1.1, n=32) permitted a simple correlation with a first-order approximation: (predicted maintenance dose) =-2.009× (initial INR) +6.172 (R²=0.706, p<0.001). Conclusion We developed a simple formula for predicting the maintenance dose of warfarin using the initial response of the INR to low-dose warfarin.

Oral Anticoagulant Therapy-When Art Meets Science

Anticoagulant treatment is extremely important and frequently encountered in the therapy of various cardiovascular diseases. Vitamin K antagonists (VKA) are in use for the prevention and treatment of arterial and venous thromboembolism, despite the introduction of new direct-acting oral anticoagulants (NOAC). The VKA still have the clear recommendation in patients with a mechanical prosthetic heart valve replacement or moderate to severe mitral stenosis of the rheumatic origin, in deep vein thrombosis associated with congenital thrombophilia, and in cases where NOAC are prohibited by social condition (financial reason) or by comorbidities (extreme weight, severe renal or liver disease). VKA dosing required to reach the targeted therapeutic range varies largely between patients (inter-individual variability). This inter-individual variability depends on multiple environmental factors such as age, mass, diet, etc. but it is also influenced by genetic determinism. About 30 genes implicated in the metabolism coumarins derivatives were identified, the most important being CYP2C9 and VKORC, each with several polymorphisms. Herein, we review the data regarding genetic alterations in general and specific populations, highlight the diagnosis options in particular cases presenting with genetic alteration causing higher sensitivity and/or resistance to VKA therapy and underline the utility of NOAC in solving such rare and difficult problems.

Combination index of the concentration and in vivo antagonism activity of racemic warfarin and its metabolites to assess individual drug responses

The present study was undertaken to examine whether in vivo vitamin K epoxide reductase complex 1 (VKOR) "actual" antagonism activity, calculated by the concentrations and the reported anticoagulant activities of the R- and S-warfarin enantiomers and their metabolites, correlates with the weekly dose of warfarin. Five patients under palliative care were enrolled in our study and 20 serum samples were analyzed by an enantioselective high-performance liquid chromatography-ultraviolet detection method. In vivo VKOR inhibition activities of S-warfarin, R-warfarin, 7- and 10-hydroxywarfarin were calculated as the ratio of drug or metabolite concentration to the IC₅₀. The mean drug concentrations (± SD) of S- and R-warfarin, 7-hydroxywarfarin and 10-hydroxywarfarin were 334 ± 154 ng/ml, 370 ± 115 ng/ml, 42 ± 15 ng/ml and 80 ± 44 ng/ml, respectively. Then, in vivo VKOR actual antagonism activities of S- and R-warfarin, 7-hydroxywarfarin and 10-hydroxywarfarin were calculated. Good correlation (R² = 0.69-0.72) was obtained between the weekly warfarin dose and the ratios of INR/actual antagonism activity, while poor correlation was observed between the weekly warfarin dose and INR (R² = 0.32) or the activities (R² = 0.17-0.21). Actual antagonism activities along with the INR correlated well with the warfarin dose. This parameter may be useful for predicting or altering warfarin doses, although further verification in a larger study is required.

Pharmacogenetics of anticoagulants used for stroke prevention in patients with atrial fibrillation

Introduction: The inclusion of pharmacogenetics alongside clinical information in anticoagulant therapy offers the opportunity for a tailored approach to treatment according to individual patient characteristics. Areas covered: Literature was searched using PubMed database, focusing on pharmacogenetics of oral anticoagulants. Original research articles and review articles in English language were included in the literature reviewed. This article includes all information available for the genetic cause of inter-individual variability in anticoagulation response to oral anticoagulant drugs. The pharmacogenetics of VKAs and NOACs are described in detail. Expert opinion: There have been numerous studies focusing on the pharmacogenetics of VKAs, particularly warfarin. Current evidence suggests that known genetic and clinical factors explain a large proportion of the inter-individual variability in response to warfarin. Pharmacogenetic-based algorithms have been validated to determine their clinical utility with equivocal results. To date, only a limited number of mostly small studies on the pharmacogenetics of NOACs exists. The latter have highlighted genetic polymorphisms in specific genes that may affect clinical outcomes. Further evaluations of these polymorphisms are needed before firm conclusions can be drawn about the significance of pharmacogenetics on NOAC therapy.

Quality of INR control and switching to non-Vitamin K oral anticoagulants between women and men with atrial fibrillation treated with Vitamin K Antagonists in Spain. A population-based, real-world study

BACKGROUND

Worldwide, there is growing evidence that quality of international normalized ratio (INR) control in atrial fibrillation patients treated with Vitamin K Antagonists (VKA) is suboptimal. However, sex disparities in population-based real-world settings have been scarcely studied, as well as patterns of switching to second-line Non-VKA oral anticoagulants (NOAC). We aimed to assess the quality of INR control in atrial fibrillation patients treated with VKA in the region of Valencia, Spain, for the whole population and differencing by sex, and to identify factors associated with poor control. We also quantified switching to Non-VKA oral anticoagulants (NOAC) and we identified factors associated to switching.

METHODS

This is a cross-sectional, population-based study. Information was obtained through linking different regional electronic databases. Outcome measures were Time in Therapeutic Range (TTR) and percentage of INR determinations in range (PINRR) in 2015, and percentage of switching to NOAC in 2016, for the whole population and stratified by sex.

RESULTS

We included 22,629 patients, 50.4% were women. Mean TTR was 62.3% for women and 63.7% for men, and PINNR was 58.3% for women and 60.1% for men (p<0.001). Considering the TTR<65% threshold, 53% of women and 49.3% of men had poor anticoagulation control (p<0.001). Women, long-term users antiplatelet users, and patients with comorbidities, visits to Emergency Department and use of alcohol were more likely to present poor INR control. 5.4% of poorly controlled patients during 2015 switched to a NOAC throughout 2016, with no sex differences.

CONCLUSION

The quality of INR control of all AF patients treated with VKA in 2015 in our Southern European region was suboptimal, and women were at a higher risk of poor INR control. This reflects sex disparities in care, and programs for improving the quality of oral anticoagulation should incorporate the gender perspective. Clinical inertia may be lying behind the observed low rates of switching in patient with poor INR control.

Pharmacogenomics of Novel Direct Oral Anticoagulants: Newly Identified Genes and Genetic Variants

Direct oral anticoagulants (DOAC) have shown an upward prescribing trend in recent years due to favorable pharmacokinetics and pharmacodynamics without requirement for routine coagulation monitoring. However, recent studies have documented inter-individual variability in plasma drug levels of DOACs. Pharmacogenomics of DOACs is a relatively new area of research. There is a need to understand the role of pharmacogenomics in the interpatient variability of the four most commonly prescribed DOACs, namely dabigatran, rivaroxaban, apixaban, and edoxaban. We performed an extensive search of recently published research articles including clinical trials and in-vitro studies in PubMed, particularly those focusing on genetic loci, single nucleotide polymorphisms (SNPs), and DNA polymorphisms, and their effect on inter-individual variation of DOACs. Additionally, we also focused on commonly associated drug-drug interactions of DOACs. CES1 and ABCB1 SNPs are the most common documented genetic variants that contribute to alteration in peak and trough levels of dabigatran with demonstrated clinical impact. ABCB1 SNPs are implicated in alteration of plasma drug levels of rivaroxaban and apixaban. Studies conducted with factor Xa, ABCB1, SLCOB1, CYP2C9, and VKORC1 genetic variants did not reveal any significant association with plasma drug levels of edoxaban. Pharmacokinetic drug-drug interactions of dabigatran are mainly mediated by p-glycoprotein. Strong inhibitors and inducers of CYP3A4 and p-glycoprotein should be avoided in patients treated with rivaroxaban, apixaban, and edoxaban. We conclude that some of the inter-individual variability of DOACs can be attributed to alteration of genetic variants of gene loci and drug-drug interactions. Future research should be focused on exploring new genetic variants, their effect, and molecular mechanisms that contribute to alteration of plasma levels of DOACs.

Clinical and genetic factors influencing acenocoumarol dosing: a cross-sectional study

: Coumadin oral anticoagulants are widely used in multiple clinical scenarios. Their narrow therapeutic range and a dosing strategy based on 'a posteriori' algorithms, pose them as an interesting group for prediction modelling research. Extensive literature explaining the association between clinical and genetic variables with the dose of warfarin have been published. Limited information exists regarding these factors and acenocoumarol dosing. The aim of the study is to explain through clinical/genetic variables, the weekly dose of acenocoumarol necessary for achieving stable anticoagulation status. We performed a cross-sectional study enrolling adults under treatment with acenocoumarol with at least three consecutive INRs between 2 and 3. To explain the association between demographic, clinical and genotype data (VKORC1, CYP2C9 and CYP4F2) and the mean weekly dose of acenocoumarol, we performed a multiple linear regression model. In our cohort, a higher age, the presence of atrial fibrillation, chronic renal failure and VKORC1 haplotype A were associated with a lower mean weekly dose of acenocoumarol. On the other side, a higher weight was associated with a higher weekly dose. Amongst anticoagulated adult patients, VKORC1 genotype and baseline clinical factors can explain acenocoumarol dosing, and therefore, help clinicians while deciding the initial anticoagulant dose.

Pharmacogenetics of warfarin dosing in patients of African and European ancestry

Despite the introduction of direct acting oral anticoagulants, warfarin remains the most commonly prescribed oral anticoagulant. However, warfarin therapy is plagued by the large inter- and intrapatient variability. The variability in dosing fueled research to identify clinical and genetic predictors and develop more accurate dosing algorithms. Observational studies have demonstrated the significant impact of single nucleotide polymorphisms in CYP2C9 and VKORC1 on warfarin dose in patients of European ancestry and African-Americans. This evidence supported the design and conduct of clinical trials to assess whether genotype-guided dosing results in improved anticoagulation control and outcomes. The trial results have shown discordance by race, with pharmacogenetic algorithms improving dose and anticoagulation control among European ancestry patients compared with African-American patients. Herein, we review the evidence from observational and interventional studies, highlight the need for inclusion of minority race groups and propose the need to develop race specific dosing algorithms.

Impact of incorporating ABCB1 and CYP4F2 polymorphisms in a pharmacogenetics-guided warfarin dosing algorithm for the Brazilian population

PURPOSE

Interpatient variation of warfarin dose requirements may be explained by genetic variations and general and clinical factors. In this scenario, diverse population-calibrated dosing algorithms, which incorporate the main warfarin dosing influencers, have been widely proposed for predicting supposed warfarin maintenance dose, in order to prevent and reduce adverse events. The aim of the present study was to evaluate the impact of the inclusion of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms as additional covariates in a previously developed pharmacogenetic-based warfarin dosing algorithm calibrated for the Brazilian population.

METHODS

Two independent cohorts of patients treated with warfarin (n = 832 and n = 133) were included for derivation and replication of the algorithm, respectively. Genotyping of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms was performed by polymerase chain reaction followed by melting curve analysis and TaqMan® assay, respectively. A multiple linear regression was performed for the warfarin stable doses as a dependent variable, considering clinical, general, and genetic data as covariates.

RESULTS

The inclusion of ABCB1 and CYP4F2 polymorphisms was able to improve the algorithm's coefficient of determination (R²) by 2.6%. In addition, the partial determination coefficients of these variants revealed that they explained 3.6% of the warfarin dose variability. We also observed a marginal improvement of the linear correlation between observed and predicted doses (from 59.7 to 61.4%).

CONCLUSION

Although our study indicates that the contribution of the combined ABCB1 and CYP4F2 genotypes in explaining the overall variability in warfarin dose is not very large, we demonstrated that these pharmacogenomic data are statistically significant. However, the clinical relevance and cost-effective impact of incorporating additional variants in warfarin dosing algorithms should be carefully evaluated.