Fluvoxamine for COVID-19 ICU patients?Vladimir TrkuljaDepartment of PharmacologyZagreb University School of MedicineŠalata 11, Zagreb, Croativladimir.trkulja@mef.hrNumber of words: 800Number of figures/tables: 1To the Editor,I read with interest a recently BJCP-accepted manuscript on the use of fluvoxamine in COVID-19 patients who needed admission to an intensive care unit (ICU) 1. It was instructive to read about the pre-existing clinical experience and about possible mechanisms of presumed benefits of fluvoxamine in COVID-19. However, attention needs to be drawn to the suggested effect of fluvoxamine quantified as a 40% reduction in instantaneous risk of death. The authors report1 on a cohort (n=51) of patients who, upon ICU admission, were treated with oral fluvoxamine added to the standard of care (SoC) (3x100 mg/day over 15 days, then 2x50 mg/day over 7 days), and who were compared to a cohort (n=51) of SoC-only patients. The two cohorts were said to be matched 1. Based on reported data 1, it appears that the patients were matched exactly in respect to gender and COVID-19 vaccination status, and, seemingly, on a rather narrow age-caliper, but the matching method was not reported 1; not reported was also a measure of matching adequacy – standardized difference (d ), a preferred method of balance assessment (adequate if d <0.1) since independent of the sample size 2. Based on the reported data1, for example, the fluvoxamine – SoC d regarding body mass index was -0.30 (-0.31 in women and -0.29 in men); also, d=-0.122 regarding history of diabetes,d= -0.350 regarding history of treated hypertension,d=-0.11 regarding on-admission APACHE score – all suggesting a considerable imbalance between the two cohorts (lower values in the fluvoxamine cohort). The authors provide Kaplan-Meier curves of time-to-death (or ICU discharge) but without the numbers at risk1. Still, data could be read from the graphs and curves reconstructed (Figure 1A):(i) the first marked difference between the treated and controls occurs during the first 7 days of observation – 3 patients died and 3 were censored in the former, and 11 died and 4 were censored the latter cohort (Figure 1A). This difference in deaths (3 vs. 11) did not change over the entire later period since the overall difference in the number of deaths was 9 (30/51 in treated vs. 39/51 in controls). This would indicate a very rapid-onset (and subsequently “lost”) effect of fluvoxamine, which does not seem pharmacologically plausible. The assumed fluvoxamine mechanisms1 are not of the immediate-onset type; with a 3x100 mg/day dosing, elimination half-life is likely to extend well beyond 30 hours, hence steady-state would be achieved only after 7-10 days 3. Combined with the baseline imbalance between groups, this indicates that the initial separation of the two curves – more or less preserved throughout the entire subsequent period - was likely not attributable to fluvoxamine; (ii) after day 21, and particularly after day 28, the numbers at risk were very low, and after day 35 there were no further events (Figure 1A), hence accounting for the entire curve is likely misleading 4; (iii) although the curves do not cross (Figure 1A), they indicate a possibility that hazard ratio varied over time. Hazard ratio as generated in a Cox proportional hazard model (as done by the authors) is an average of values that can change over time5; it is also inherently prone to selection bias and, even in absence of confounding its interpretation is not straightforward5. This holds for randomized and particularly for non-randomized settings 5. Reconstructed data depicted in Figure 1A were used to fit a complementary log-log model for continuous time process taking into account the first 35 days (no events after that point): the method treats time as a continuous but more “coarsely” measured variable, in intervals of identical length (in this case 7-day intervals, i.e., weeks); based on assumption of constant hazard within the interval, the method provides period-specific (for weeks 1-5) hazard ratios 6, which is likely a preferable option 5. Figure 1B depicts estimated probabilities of death and HRs: it is only during week 1 that the hazard appeared lower in treated – a period during which, as elaborated, fluvoxamine most likely had no effect. Finally, authors fitted a multivariable Cox model 1to substantiate the fluvoxamine effect. With a total of 15 independents in a study with 102 subjects, the model was likely overfitted and susceptible to bias arising from over(unnecessary)-adjustments 7. But more importantly, it included adjustment for renal replacement therapy (RRT), which was actually one of the outcomes. Inadequacy of adjustments for post-exposure outcomes as if they were baseline covariates has been extensively elaborated 8 and almost inevitably results in a considerable bias, regardless of whether the respective variable was actually a mediator or a collider 8. Such adjustments require implementation of marginal structural models or some of the g-estimation methods 9.Overall, the reported difference between the two cohorts of patients is more likely bias arising from design and analysis than evidence supporting a causal effect of fluvoxamine.ReferencesČalušić M, Marčec R, Lukša L et al. Safety and efficacy of fluvoxamine in COVID-19 ICU patients: an open label, prospective cohort trial with matched controls. Br J Clin Pharmacol . 2021; doi: 10.1111/bcp.15126.Stuart EA. Matching methods for causal inference: a review and a look forward. Stat Sci . 2010; 25(1):1-21.Hiemke C, Hartter S. Pharmacokinetics of selective serotonin reuptake inhibitors. Pharmacol Ther . 2000; 85 (1):11-28.Machin D, Cheung YB, Parmar MKB, eds. Survival analysis: a practical approach . 2nd ed. Chichester, West Sussex: John Wiley & Sons Ltd; 2006. p.38.Hernan MA. The hazards of hazard ratios. Epidemiology 2010; 21(1):13-15.Prentice RL, Gloecker LA. Regression analysis of grouped survival data with application to breast cancer data. Biometrics 1978; 34(1):57-67.Schisterman EF, Core SF, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiological studies. Epidemiology 2009; 20(4):488-495.Greenland S. Quantifying biases in causal models: classical confounding vs collider-stratification bias. Epidemiology 2003; 14(4):300-306.Hernan MA, Robins JM, eds. Causal inference: What if . 1st ed. CRC Press LLC; 2019.Figure 1 . Summary of re-analysis of survival data published in ref. 1. A . Reconstructed curves of Kaplan-Meier product-limit estimates. Data1 were read using a digitizing software, and were re-analyzed and curves were drawn using JMP 13 software (SAS Institute Inc., Cary, NC). Upward oriented ticks indicate censorings, downward oriented ticks indicate failures. ICU – intensive care unit. B . Estimated probabilities of death during weeks 1 to 5 by treatment (Fluvox – fluvoxamine) and period-specific hazard ratios (HR) with confidence intervals. A complementary log-log model was fitted to reconstituted data using SAS 9.4 for Windows (SAS Inc., Cary, NC).

Aims: Given the complexity of antithrombotic therapy guidelines especially in patients with combined antithrombotic therapy, there is a risk of inappropriate prescribing and medication errors. In order to prevent this, a multidisciplinary antithrombotic stewardship (ASP) is implemented in our hospital. The primary aim of this study is to determine the efficacy of this ASP by assessing the number of patients on combined antithrombotic therapy for whom one or more interventions are needed. Methods: A prospective cohort study in a large teaching hospital is conducted. Hospitalized patients who received combined antithrombotic therapy in which an oral anticoagulant was combined with one (double therapy) or two (triple therapy) platelet aggregation inhibitors were included. The ASP proactively evaluated the appropriateness of this combined antithrombotic therapy. If needed, ASP improved the concerned therapy. Each improvement measurement by ASP was counted as one intervention. Results: A total of 460 patients were included over a period of 12 months. 251 (54.6%) patients required at least one intervention from the ASP. The most common intervention was to define and document a maximum duration of the combined antithrombotic therapy (65.5%) instead of lifetime use of the combination, to discontinue antithrombotic therapy (19.4%) as the proper indication was lacking and to adjust the dosage (8.1%). Conclusion: As intervention was needed in more than half of the patients on combined antithrombotic therapy, it seems essential to implement an ASP that dedicated evaluates antithrombotic therapy to improve and ensure optimal use and medication safety.

Aim Dose banding is a commonly used method of dose individualisation in which all patients with similar characteristics are allocated to the same dosing group. Dose banding results in some patients receiving less intensive treatment with the potential for a reduction in therapeutic benefit (iatrogenic therapeutic failure). This study aims to explore the effects of dose banding on therapeutic success and failure. Methods This was a simulation study conducted using MATLAB. Virtual patients were simulated under a simple pharmacokinetic model with a predefined target steady-state average concentration (c_(ss,ave)). Clearance was correlated with a covariate used for dosing. Dose individualisation was based on: one-dose-fits-all, covariate based dosing, empirical dose banding, dose banding optimised for benefit:risk only and dose banding optimised for both benefit:risk and minimising iatrogenic therapeutic failure. Results The lowest and highest probabilities of target attainment (PrTA) were 46% for one-dose-fits-all and 72% for fully individualised covariate-based dosing. Neither dosing approach would result in iatrogenic therapeutic failure as lower dose intensities do not occur. Empirical dose banding performed better than once-dose-fits-all with 59% PTA but not as good as either optimised method (64-69% PrTA) while carrying a risk of iatrogenic therapeutic failure in 25% of patients. Optimising for benefit:risk (only) improved PrTA but carried a risk of iatrogenic therapeutic failure of up to 10%. Optimising for benefit:risk and minimising iatrogenic therapeutic failure provided the best balance. Conclusion Future application of dose banding needs to consider both the probability of benefit:risk as well the risk of causing iatrogenic therapeutic failure.

COVID-19 has spread globally, affecting almost 160 million individuals. Elderly and pre-existing patients (such as diabetes, heart disease and asthma), seems more susceptible to serious illness with COVID-19. Roflumilast was licensed for usage in the European Union in July 2010 as a phosphodiesterase-4 (PDE4) inhibitor. Roflumilast has been shown to decrease bleomycin-induced lung fibrosis, lung hydroxyproline, right heart thickning in animal prophylactic. The current study reviewed existing data that the PDE-4 inhibitor protects not just renal tissues but also other major organ systems after COVID-19 infection by decreasing immune cell infiltration. These immune-balancing effects of roflumilast were related with a decrease in oxidative and inflammatory burden, caspase-3 suppression, and increased PKA/cAMP levels in renal and other organ tissue.

Aim: nlmixr offers first-order conditional estimation with or without interaction (FOCE or FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin’s population pharmacokinetics with flip-flop characteristics within nlmixr framework and investigated SAEM and FOCEi’s performance with respect to bias, precision, and robustness. Method: Compartmental pharmacokinetic models were fitted. The final model was determined based on the lowest objective function value and visual inspection of goodness-of-fit plots. To examine flip-flop pharmacokinetics, k_a values of a typical concentration-time profile based on the final model were perturbed and changes in the steepness of the terminal elimination phase were evaluated. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100-times and resultant changes evaluated. Results: A one-compartment model with transit compartment for absorption best described the data. At low n, Stirling’s approximation of n! over-approximated plasma concentration unlike the log-gamma function. Flip-flop pharmacokinetics were evident as the steepness of the terminal elimination phase changed with k_a. Mean rRMSE for fixed-effect parameters was 0.932. When initial estimates were perturbed, FOCEi estimates of k_a and food effect on k_a appeared bimodal and were upward biased. Discussion: nlmixr is reliable for NLMEM even if flip-flop is present but caution should be exercised when using Stirling’s approximation for n! in the transit compartment model. SAEM was marginally superior to FOCEi in bias and precision, but SAEM was superior against initial estimate perturbations.

Background: Mycophenolate mofetil (MMF) is the most widely used second-line agent in auto-immune hepatitis (AIH). It is generally titrated up to patient response and continued for at least two years following complete liver enzyme normalization. However, in this maintenance phase individual dose adjustment to reach mycophenolic acid (MPA) exposure with the best benefit-risk probability may avoid adverse outcomes. The aim of the present study was to develop population pharmacokinetic (popPK) models and Maximum A-Posteriori Bayesian estimators (MAP-BEs) to estimate MPA inter-dose area under the curve (AUC0-12h) in AIH patients administered MMF using nonlinear mixed effect modelling. Methods: We analysed 50 MPA PK profiles from 34 different patients, together with some demographic, clinical, and laboratory test data. The median number of samples per profile, immediately preceding and following the morning MMF dose, was 7 [4 – 10]. PopPK modeling was performed using parametric, top-down, nonlinear mixed effect modelling with NONMEM 7.3. MAP-BEs were developed based on the the best popPK model and the best limited sampling strategy (LSS) selected among several. Results: The pharmacokinetic data were best described by a 2-compartment model, Erlang distribution to describe the absorption phase, and a proportional error. The best MAP-BE relied on the LSS at 0.33, 1 and 3 hours after mycophenolate mofetil dose administration and was very accurate (bias=5.6%) and precise (RMSE<20%). Conclusion: The precise and accurate Bayesian estimator developed in this study for AIH patients on MMF can be used to improve the therapeutic management of these patients.

There is a growing interest in the psychiatric properties of the dissociative anesthetic ketamine, as single doses have been shown to have fast-acting mood-enhancing and anxiolytic effects, which persist for up to a week after the main psychoactive symptoms have diminished. Therefore, ketamine poses potential beneficial effects in patients with refractory anxiety disorders, where other conventional anxiolytics have been ineffective. Ketamine is a non-competitive antagonist of the N-methyl-D-aspartate (NMDA) glutamate receptor, which underlies its induction of pain relief and anaesthesia. However, the role of NMDA receptors in anxiety reduction is still relatively unknown. To fill this paucity in the literature, this systematic review assesses the evidence that ketamine significantly reduces refractory anxiety and discusses to what extent this may be mediated by NMDA receptor antagonism. We highlight the temporary nature of the anxiolytic effects and discuss the high discrepancy among the study designs regarding many fundamental factors such as administration routes, complementary treatments, and other treatments.

Introduction: In critically ill patients, Transfusion Related Acute Lung Injury (TRALI) remains the leading cause of transfusion-related fatalities in critical care setting and associated with inflammation and oxidative stress state. Recent research raised the potential efficacy of high dose intravenous ascorbic acid in critically ill patients. Objective: The aim of this trial was to investigate the effect of high dose intravenous ascorbic acid (VC) as a targeted therapy for TRALI in terms of serum proinflammatory (interleukin-8, interleukin-1β, C-reactive protein), anti-inflammatory (interleukin-10), oxidative stress (superoxide dismutase, malondialdehyde) markers, and plasma VC levels. Secondary outcomes were oxygenation (PaO2/FiO2 ratio), vasopressor use, duration of mechanical ventilation, ICU length of stay, 7-days mortality and 28-days mortality. Methods: Eighty critically ill patients with TRALI (n=80) were randomized to receive 2.5gm/6hr intravenous vitamin C for 96 hours (ASTRALI group) or placebo. Patients were followed-up to measure the outcomes initially (T0) and at the end of treatment (T96). Results: When compared to control group, ASTRALI group at T96, showed significantly higher median of interleukin-10 (31.6 ± 25.8 Vs. 17.7 ± 12.0 pg/mL, p<0.0001) levels and superoxide dismutase (12876 ± 4627 U/L Vs. 5895 ± 6632 U/L, p<0.0001) activities, lower median C-reactive protein (76 ± 50 Vs. 89 ± 56 mg/L, p=0.033), interleukin-8 (11.8 ± 7.3, 35.5 ± 19.8 pg/mL, p<0.0001), and malondialdehyde (0.197 ± 0.034 Vs. 0.234 ± 0.074 µM/L, p=0.002) levels. Conclusion: High dose ascorbic acid was associated with significantly reduced oxidative stress, reduced pro-inflammatory markers except IL-1β, elevated anti-inflammatory marker, and elevated plasma VC levels

A document by Emma Magavern. Click on the document to view its contents.

Drug-related adverse reactions are among the main reasons for harm to patients under care worldwide and even their deaths. The pharmacovigilance system has been proven to be an effective method of avoiding or alleviating such adverse events. In 2019, after two decades of implementation of the drug-related adverse reaction reporting system, China formally implemented a pharmacovigilance system with the Pharmacovigilance Quality Management Standards and a series of supporting technical documents created to improve the safety of medication given to patients. China’s pharmacovigilance system has faced many problems and challenges during its implementation. This spontaneous reporting system is the main source of data for China’s medication vigilance activities, but it has not provided sufficiently powerful evidence for regulatory decision-making. In conformity to the health-centered drug regulatory concept, the Chinese government has accelerated the speed of examination and approval of urgently needed clinical drugs and orphan drugs along with the requirement to improve the safety supervision of these drugs after their listing. China’s marketing authorization holders（MAHs）must strengthen its pharmacovigilance capabilities as the primary responsible department for drug safety. Chinese medical schools generally lack professional courses on pharmacovigilance. The regulatory authorities have recognized such problems and have made efforts to improve the professional capacity of pharmacovigilance personnel and to strengthen cooperation with stakeholders through the implementation of an action plan of medication surveillance and the establishment of patient-based adverse events reporting system and active surveillance systems, which will help China bridge the gap to bring its pharmacovigilance practice up to standards.

Objectives We aim to seek expert opinion and gain consensus on the risks associated with a range of prescribing scenarios, preventable using e-prescribing systems, to inform the development of a simulation tool to evaluate the risk and safety of e-prescribing systems (ePRaSE). Methods We conducted a two-round eDelphi survey where expert participants were asked to score pre-designed prescribing scenarios using a five-point Likert scale to ascertain the likelihood of occurrence of the prescribing event, likelihood of occurrence of harm and the severity of the harm. Results Twenty four experts consented to participate with fifteen participants and thirteen participants completing rounds 1 and 2 respectively. Experts agreed on the level of risk associated with 136 out of 178 clinical scenarios with 131 scenarios categorised as high or extreme risk. Discussion We identified 131 extreme or high-risk prescribing scenarios that may be prevented using e-prescribing clinical decision support. The prescribing scenarios represent a variety of categories, with drug-disease contraindications, being the most frequent representing 37 (27%) scenarios and antimicrobial agents being the most common drug class representing 28 (21%) of the scenarios. Conclusion Our eDelphi study has achieved expert consensus on the risk associated with a range of clinical scenarios with most of the scenarios categorised as extreme or high risk. These prescribing scenarios represent the breadth of preventable prescribing error categories involving both basic and advanced clinical decision support. We will use the findings of this study to inform the development of the e-prescribing risk and safety evaluation tool.

Paracetamol overdose is common in developed countries but less than 10% involve large ingestions exceeding 30g or 500mg/kg. High dose acetylcysteine (NAC) has been proposed in patients taking large paracetamol overdoses based on reports of hepatotoxicity despite early initiation of NAC treatment with the commonly used 300 mg/kg intravenous acetylcysteine regimen. The evidence from cohorts of patients treated with the standard NAC regimen after large paracetamol overdoses shows that it is effective in most patients. Small studies in patients whose paracetamol concentration are above the 300mg/L nomogram line show that modification of the standard NAC regimen to provide a total of 400-500 mg/kg NAC over 21-22h may reduce the risk of hepatotoxicity (peak ALT>1000 IU/L) but the impact on development of hepatic failure, liver transplantation and mortality with this approach is presently unknown. Better risk stratification of patients taking paracetamol overdose may allow higher dose NAC and adjunctive treatments such as CYP2E1 inhibition and extracorporeal removal of paracetamol to be targeted to those patients at the highest risk of hepatotoxicity after a large paracetamol overdose.

The propellants used in metered-dose inhalers (MDIs) are powerful greenhouse gases, which account for approximately 13% of the NHS’s carbon footprint related to the delivery of care. Most MDI use is in salbutamol relievers in patients with poorly controlled disease. The UK lags behind in this regard with greater reliance on salbutamol MDI and correspondingly greater greenhouse gas emissions; roughly treble our European neighbours’. There has been a broad switch towards MDIs in the UK over the last 20 years to reduce financial costs such that two-thirds of asthma patients in the UK are on treatment dominated by salbutamol MDI. Strategies that replace overuse of reliever MDIs with regimes emphasising inhaled corticosteroids have the potential to improve asthma control alongside significant reductions in greenhouse gas emissions. Real-world evidence shows that once-daily long-acting combination dry-powder inhalers can improve compliance, asthma control and reduce the carbon footprint of care. Similarly, maintenance and reliever therapy (MART) which uses combination reliever and inhaled steroids in one device (usually a dry-powder inhaler) can simplify therapy, improve asthma control and reduce greenhouse gas emissions. Both treatment strategies are popular with patients, most of whom are willing to change treatment to reduce their carbon footprint. By focussing on patients who are currently using high amounts of salbutamol MDI, and prioritising inhaled steroids via dry-powder inhalers, there are golden opportunities to make asthma care more effective, safer and greener.

Aim: The placebo effect and the specific effect are often thought to add up (additive model). Whether this is true or whether there is an interaction between the two, can modify the external validity of a trial. This assumption of additivity was tested by Kleijnen et al. in 1994 but the data produced since then has not been synthetized. In this review, we aimed to systematically review the literature to determine whether additivity held. Methods: We searched Medline and Psychinfo up to 10/01/2019. Studies using the balanced placebo design (BPD), testing two different strengths of placebos, were included. The presence of interaction was evaluated by comparing each group in BPD with analysis of variance or covariance. Results: 30 studies were included and the overall risk of bias was high: four found evidence of additivity and 16 studies found evidence of interaction (seven had evidence of positive additivity). Conclusion: Evidence of additivity between placebo and specific features of treatments was rare in our sample. For ailments that are placebo-responsive, pragmatic trials should be preferred to increase their external validity.

It is unfortunately true that clinicians lack the necessary evidence to know how to use medications properly in large sections of the population, and we do not have optimal drugs to use in many Neglected Tropical Diseases (NTDs). NTD’s often disproportionately affect neglected populations such as children and pregnant women. As reliable access to safe, effective preventives and treatments can break the cycle of poverty, illness, and ensuing debility that further perpetuates poverty, it is of paramount importance to investigate and develop new medicines for neglected populations suffering from NTDs. Furthermore, there is not only a need to develop and evaluate novel therapies, but also to ensure that these are affordable, available, and adapted to the communities who need them. With this editorial, the British Pharmacological Society hereby launches a call for high-quality articles focusing on NTDs in special populations, to facilitate the reversal of this dual neglect.

Low- and middle-income countries (LMIC) face unique challenges with regard to the establishment of robust pharmacovigilance systems capable of generating data to inform healthcare policy and practice. These include the limited integration and reliance of pharmacovigilance systems across LMIC despite recent efforts to harmonize pharmacovigilance rules and regulations in several regional economic communities; the need to translate reporting tools into numerous local languages; low numbers of healthcare providers relative to number of patients, with very short consultation times; scarcity of well-trained pharmacovigilance personnel with little or no budgetary support for these activities from national governments; high turnover of pharmacovigilance staff whose training involves a substantial amount of resources; little awareness of pharmacovigilance among healthcare workers, decision makers and consumers; very low spontaneous reporting rates with poor quality reports which hinders robust signal detection analyses; little collaboration between public health programmes and national medicines regulatory authorities; limited investment in pharmacovigilance activities especially during mass drug administration for neglected tropical diseases; high uptake of herbal and traditional medication, mostly by self-medication; disruptive political conflicts jeopardizing fragile systems; and little or no access to drug utilization data which makes it difficult to reliably estimate the true safety risks of medicine use. This review summarises the specific challenges and areas of progress in pharmacovigilance in LMIC with special focus on the situation in Africa.

Aim. Cancer patients with reduced dihydropyrimidine dehydrogenase (DPD) activity are at increased risk of severe fluoropyrimidine (FP)-related adverse events (AE). Guidelines recommend FP dosing adjusted to genotype-predicted DPD activity based on four DPYD variants (rs3918290, rs55886062, rs67376798, rs56038477). We evaluated relationship between three further DPYD polymorphisms [c.496A>G (rs2297595), *6 c.2194G>A (rs1801160) and *9A c.85T>C (rs1801265)] and the risk of severe AEs. Methods. Consecutive FP-treated adult patients were genotyped for “standard” and tested DPYD variants, and for UGT1A1*28 if irinotecan was included, and were monitored for the occurrence of grade ≥3 (National Cancer Institute Common Terminology Criteria) vs. grade 0-2 AEs. For each of the tested polymorphisms, variant allele carriers were matched to respective wild type controls (optimal full matching combined with exact matching, in respect to: age, sex, type of cancer, type of FP, DPYD activity score, use of irinotecan/UGT1A1, adjuvant therapy, radiotherapy, biological therapy and genotype on the remaining three tested polymorphisms). Results. Of the 503 included patients (82.3% colorectal cancer), 283 (56.3%) developed grade ≥3 AEs, mostly diarrhea and neutropenia. Odds of grade ≥3 AEs were higher in c.496A>G variant carriers (n=127) than in controls (n=376) [OR=5.20 (95%CI 1.88-14.3), Bayesian OR=5.24 (95% CrI 3.06-9.12)]. Odds tended to be higher in *6 c.2194G>A variant carries (n=58) than in controls (n=432) [OR=1.88 (0.95-3.73), Bayesian OR=1.90 (1.03-3.56)]. *9A c.85T>G did not appear associated with grade ≥3 AEs (206 variant carriers vs. 284 controls). Conclusion. DPYD c.496A>G variant might need to be considered for inclusion in the DPYD genotyping panel.

Climate change continues to pose a dangerous threat to human health. However, not only is health impacted by this crisis, healthcare itself adds to the problem, through significant contributions to green house gas emissions. In the UK, the National Health Service (NHS) is responsible for an estimated 4% of the overall national carbon footprint. Medicines account for a quarter of this and whilst they are vital in in health now, through sustainable use they can also positively influence the environmental health of the future. In this review, we explore how clinical pharmacologists and other health care professionals can practice sustainable medicines use or eco-pharmaco-stewardship. We will discuss current and near future environmental practices within the NHS, which we suspect will resonate with other health systems. We will suggest approaches for championing eco-pharmaco-stewardship in drug manufacturing, clinical practices and patient use, to achieve a more a sustainable healthcare system.