A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study.

BACKGROUND: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. METHODS: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING: European Union Horizon 2020.

Psychiatric medication use before and after the onset of type 1 diabetes in children and adolescents: A population-based cohort study.

BACKGROUND: Several studies showed a bidirectional association between type 2 diabetes and psychiatric disorders in adults. Because there is limited information on the association between type 1 diabetes (T1D) and psychiatric disorders (including psychiatric medication use) in children and adolescents, we assessed frequency of use of these medications before and after the onset of T1D. METHODS: A population-based cohort study was conducted in the Dutch PHARMO Record Linkage System (1999-2009). Children and adolescents (<19 years) with at least 2 insulin dispensings from community pharmacies (T1D cohort, N = 925) were matched by age and sex (reference cohort without insulin use, N = 3591). The 5-year prevalence of psychiatric medication use (psycholeptics [ATC N05] and psychoanaleptics [ATC N06]) before and after onset of T1D were estimated, compared, and stratified by age, sex, and medication subgroup. RESULTS: The mean age of study participants was 10.1 years and 51% were boys. The 5-year prevalence of psychiatric medication use before the index date was significantly higher in the T1D cohort than in the reference cohort (7.2% vs 4.7%, respectively; P = .002) with the same pattern after developing T1D (10.4% vs 7.9%, respectively; P = .015). In both cohorts, adolescents (15-19 years) and boys had higher prevalences of use. This increased prevalence of psychiatric medication use both before and after the index date in T1D cohort was mainly driven by an increased use of psycholeptics (predominantly anxiolytics). CONCLUSIONS: Children with T1D were more likely to use psychiatric medication in the years before and after the onset of T1D which was mainly driven by psycholeptic use.

Medication Discontinuation in Patients After Discharge From a Psychiatric Hospital.

BACKGROUND: Patients discharged from psychiatric hospitals may be at risk for intentional or unintentional discontinuation of their medication. OBJECTIVE: To describe and assess the discontinuation of, and changes to, psychiatric and/or somatic medication in patients after discharge from psychiatric hospitals. METHODS: A retrospective follow-up study was conducted in patients discharged from 4 psychiatric hospitals in The Netherlands between 2006 and 2009. Patients' medication use during the last 2 days of hospitalization was compared with medication dispensed during the 3 months following discharge. Changes in psychiatric and somatic medication were investigated and defined as medication discontinuation, start, or switch. Patients were classified as continuing users, when there were no changes to the medication after discharge. Relative risks with 95% confidence intervals to measure differences in discontinuation were estimated using Cox regression analysis. RESULTS: This study included 1324 patients, 69.8% of whom discontinued medication, and 9.7% switched one or more medications. Nearly half (47.4%) of all patients started a medication other than that dispensed during the last 2 days of hospitalization, and 13.7% of all patients experienced no changes to their medication regimen. Approximately 40% of the patients discontinued one or more medications for chronic conditions. From these, 68% discontinued psychiatric medications and 49.4% discontinued somatic medications. A quarter (25.2%) of the 644 patients discontinued using antipsychotics. More than a quarter (28.4%) of the 292 patients using medications for cardiovascular problems discontinued. Patients using as-needed medication prior to discharge were more likely to discontinue their medication (relative risk = 1.85; 95% confidence interval = 1.55-2.20). CONCLUSIONS: Discharge from a psychiatric hospital led to medication discontinuation in approximately 70% of all patients. Approximately 40% of the patients discontinued medications for chronic conditions. Discontinuation of somatic medication was more frequent than discontinuation of psychiatric medication, and risk of discontinuation was lower for patients with depressive and anxiety disorders. Although medication discontinuation can be deliberate it is alarming that a quarter of our patients using antipsychotics and cardiovascular medications discontinued their use, both of which are meant for chronic conditions.

Discontinuation of somatic medication during psychiatric hospitalization.

BACKGROUND: Psychiatric hospitalization can increase the risk of discontinuation of pharmacotherapy, which may negatively influence patients' health. OBJECTIVE: To investigate the association between psychiatric hospitalization and discontinuation of somatic medication. METHODS: A retrospective crossover study was performed in patients admitted to a psychiatric hospital (index date), who had got somatic medication dispensed during the 3 months prior to hospitalization. Discontinuation of somatic medication was investigated at the following time points: index date and 3, 6, and 9 months before the index date. Relative risks (RR) with 95% confidence intervals (95% CIs) of discontinuing somatic medication at the index date versus the time points before the index date were estimated using Cox regression. RESULTS: In all, 471 hospitalized patients were included in the study; 38.9% of the patients were discontinuers on the index date. RR for discontinuation of ≥1 somatic medication was 1.88 (95% CI=1.55-2.27) at the index date compared with the other time points and highest for patients<45 years (RR=2.83; 95% CI=1.92-4.18). CONCLUSIONS: Psychiatric hospitalization was associated with an almost doubled risk of discontinuation of somatic medication. Future studies should address the influence of discontinuation of care on patients' health.

A case report: Management of carbamazepine intoxication using hemodialysis followed by continuous venovenous hemodialysis.

An 18-year-old woman presented to the emergency department. She had ingested 43 extended-release tablets of carbamazepine 400 mg. Although the patient had high carbamazepine plasma levels and classified as severe intoxication, her clinical symptoms were less severe than expected. With the combination of hemodialysis and continuous venovenous hemodialysis in addition to usual care, including multiple-dose activated charcoal, a fast decrease (within 3 days) in carbamazepine plasma levels to levels in the therapeutic range was achieved. Only one session of hemodialysis was performed because the clinical status of the patient stabilized. In retrospect, the patient did not suffer severe toxicological symptoms from carbamazepine. Therefore, continuous venovenous hemodialysis could have been discontinued earlier. On the other hand, the fast decrease in carbamazepine plasma levels during extracorporeal treatment may have prevented the development of severe or rebound toxicological symptoms. This case report adds evidence to the successful management of carbamazepine intoxication using hemodialysis followed by continuous venovenous hemodialysis.

Whole Body Physiologically Based Pharmacokinetic Model to Explain A Patient With Drug-Drug Interaction Between Voriconazole and Flucloxacillin.

BACKGROUND AND OBJECTIVES: Voriconazole administered concomitantly with flucloxacillin may result in subtherapeutic plasma concentrations as shown in a patient with Staphylococcus aureus sepsis and a probable pulmonary aspergillosis. After switching our patient to posaconazole, therapeutic concentrations were reached. The aim of this study was to first test our hypothesis that flucloxacillin competes with voriconazole not posaconazole for binding to albumin ex vivo, leading to lower total concentrations in plasma. METHODS: A physiologically based pharmacokinetic (PBPK) model was then applied to predict the mechanism of action of the drug-drug interaction (DDI). The model included non-linear hepatic metabolism and the effect of a severe infectious disease on cytochrome P450 (CYP) enzymes activity. RESULTS: The unbound voriconazole concentration remained unchanged in plasma after adding flucloxacillin, thereby rejecting our hypothesis of albumin-binding site competition. The PBPK model was able to adequately predict the plasma concentration of both voriconazole and posaconazole over time in healthy volunteers. Upregulation of CYP3A4, CYP2C9, and CYP2C19 through the pregnane X receptor (PXR) gene by flucloxacillin resulted in decreased voriconazole plasma concentrations, reflecting the DDI observations in our patient. Posaconazole metabolism was not affected, or was only limitedly affected, by the changes through the PXR gene, which agrees with the observed plasma concentrations within the target range in our patient. CONCLUSIONS: Ex vivo experiments reported that the unbound voriconazole plasma concentration remained unchanged after adding flucloxacillin. The PBPK model describes the potential mechanism driving the drug-drug and drug-disease interaction of voriconazole and flucloxacillin, highlighting the large substantial influence of flucloxacillin on the PXR gene and the influence of infection on voriconazole plasma concentrations, and suggests a more limited effect on other triazoles.

Pharmacogenetics and phenoconversion: the influence on side effects experienced by psychiatric patients.

Introduction: Preventing side effects is important to ensure optimal psychopharmacotherapy and therapeutic adherence among psychiatric patients. Obtaining the pharmacogenetic profile of CYP2C19 and CYP2D6 can play an important role in this. When the genotype-predicted phenotype shifts because of the use of co-medication, this is called phenoconversion. The aim was to study the influence of the pharmacogenetic (PGx) profile and phenoconversion on side effects experienced by psychiatric patients. Methods: A retrospective cohort study was performed using data from 117 patients from a psychiatric outpatient clinic. Patients were genotyped with a psychiatric PGx panel and side effects were evaluated using the Udvalg for Kliniske Undersølgelser side effects rating scale (UKU). Results: Of all patients, 10.3% and 9.4% underwent phenoconversion (any shift in predicted phenotype) for CYP2C19 and CYP2D6 respectively. No significant associations were found between the phenotype and UKU-score. 75% of the patients with an Intermediate metabolizer (IM) or Poor metabolizer (PM) phenoconverted phenotype of CYP2C19 experienced nausea and vomiting compared to 9.1% of the Normal metabolizer (NM) and Ultrarapid metabolizer (UM) patients (p = 0.033). 64% of the patients with an IM or PM phenoconverted phenotype of CYP2D6 experienced the side effect depression compared to 30.4% NMs and UMs (p = 0.020). CYP2D6 IM and PM patients had a higher concentration-dose ratio than NM patients (p < 0.05). Discussion: This study underlines the importance to consider phenoconversion when looking at a patient's genotype. This is important for a better prediction of the phenotype and preventing possible side effects under a specific psychopharmacotherapy.

Optimizing Antiviral Dosing for HSV and CMV Treatment in Immunocompromised Patients.

Herpes simplex virus (HSV) and cytomegalovirus (CMV) are DNA viruses that are common among humans. Severely immunocompromised patients are at increased risk of developing HSV or CMV disease due to a weakened immune system. Antiviral therapy can be challenging because these drugs have a narrow therapeutic window and show significant pharmacokinetic variability. Above that, immunocompromised patients have various comorbidities like impaired renal function and are exposed to polypharmacy. This scoping review discusses the current pharmacokinetic (PK) and pharmacodynamic (PD) knowledge of antiviral drugs for HSV and CMV treatment in immunocompromised patients. HSV and CMV treatment guidelines are discussed, and multiple treatment interventions are proposed: early detection of drug resistance; optimization of dose to target concentration by therapeutic drug monitoring (TDM) of nucleoside analogs; the introduction of new antiviral drugs; alternation between compounds with different toxicity profiles; and combinations of synergistic antiviral drugs. This research will also serve as guidance for future research, which should focus on prospective evaluation of the benefit of each of these interventions in randomized controlled trials.

The efficacy of antipsychotics in the treatment of physical aggressive behavior in patients with dementia in nursing homes.

Patients with dementia often suffer from behavioral changes. A common behavioral change is acute physical aggressive behavior which is the most distressing change. This can lead to harm, which is especially problematic in nursing homes. Despite the serious safety concerns, antipsychotics are often prescribed to combat this problem. This article is aimed to review the evidence of the efficacy of utilizing antipsychotics in acutely treating physical aggressive behavior in patients with dementia in nursing homes. Therefore, a systematic literature search was performed. The results demonstrated that a meta-analysis confirmed statistically significant reduction in physical aggression when risperidone was compared to placebo. However, a randomized controlled trial showed no change in physical aggressive behavior between quetiapine and placebo. More research is needed to fully investigate the benefits of physical aggressive behavior and safety concerns of all the antipsychotics in patients with dementia in nursing homes.

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.

Predicting rehospitalization in patients treated with antipsychotics: a prospective observational study.

BACKGROUND: Prediction of rehospitalization in patients treated with antipsychotics is important for identifying patients in need of additional support to prevent hospitalization. Our aim was to identify factors that predict rehospitalization in patients treated with antipsychotics at discharge from a psychiatric hospital. METHODS: Adult patients suffering from schizophrenia, psychotic or bipolar I disorders who had been hospitalized in a psychiatric hospital for ⩾7 days and were treated with oral antipsychotics at discharge were included. The main outcome was rehospitalization within 6 months after discharge. A prediction model for rehospitalization was constructed including: patient/disease and medication characteristics, patients' beliefs about medicines, and healthcare-professional-rated assessment for all patients. The patients were stratified by diagnosis (schizophrenia and nonschizophrenia). Area under the receiver operating characteristic curve (AUCROC) was also assessed. RESULTS: A total of 87 patients were included and 33.3% of them were rehospitalized within 6 months after discharge. The variables that predicted rehospitalization were duration of hospitalization, patients' attitude towards medicine use, and healthcare-professional-rated assessment with an AUCROC of 0.82. Rehospitalization for patients with schizophrenia could be predicted (AUCROC = 0.71) by the Global Assessment of Functioning score, age, and harm score. Rehospitalization was predicted (AUCROC = 0.73) for nonschizophrenia patients with, for example rehospitalization predicted by the nurse. CONCLUSIONS: Rehospitalization was predicted by a combination of variables from the patient/disease and medication characteristics, patients' attitude towards medicine use, and healthcare-professional-rated assessment. These variables can be assessed relatively easily at discharge to predict rehospitalization within 6 months.