Allogeneic adipose tissue-derived mesenchymal stem cells in ischaemic stroke (AMASCIS-02): A phase IIb, multicentre, double-blind, placebo-controlled clinical trial protocol

Introduction Stroke is a serious public health problem, given it is a major cause of disability worldwide despite the spread of recanalisation therapies. Enhancement of brain plasticity with stem cell administration is a promising innovative therapy to reduce sequelae in these patients. Methods and analysis We have developed a phase IIb, multicentre, randomised, double-blind, placebo-controlled clinical trial protocol to evaluate the safety and efficacy of intravenous administration of allogeneic adipose tissue-derived mesenchymal stem cells (AD-MSCs) in patients with acute ischaemic stroke, concurrently with conventional stroke treatment. Thirty patients will be randomised on a 1:1 basis to receive either intravenous placebo or allogeneic AD-MSCs as soon as possible within the first 4 days from stroke symptom onset. Patients will be followed up to 24 months after randomisation. The primary objective is the safety assessment of early intravenous administration of allogeneic AD-MSCs by reporting all adverse events and neurological or systemic complications in both treatment groups. Secondary objectives assess efficacy of early intravenous AD-MSC treatment in acute ischaemic stroke by evaluating changes in the modified Rankin Scale and the National Institutes of Health Stroke Scale throughout the follow-up period. In addition, brain repair biomarkers will be measured at various visits. Ethics and dissemination This clinical trial has been approved by the Clinical Research Ethics Committee of La Paz University Hospital (Madrid, Spain) and by the Spanish Agency of Medication and Health Products and has been registered in Eudra CT (2019-001724-35) and ClinicalTrials.gov (NCT04280003). Study results will be disseminated through peer-reviewed publications in Open Access format and at conference presentationsThis clinical trial has been promoted by the La Paz University Hospital Institute for Health Research—IdiPAZ (La Paz University Hospital—Universidad Autónoma de Madrid) and sponsored from a competitive grant from the Carlos III Health Institute Healthcare Research Fund, and cofunded by the European Regional Development Fund (ERDF) 'A way to make Europe'/'Investing in your future' (PIC18/00016). This clinical trial has been supported by Plataforma Española de Investigación Clínica y Ensayos Clínicos, SCReN (Spanish Clinical Research Network), funded by Carlos III Health Institute-General Subdirection for Evaluation and Promotion of Research, research PT17/0017/0013; State Plan for Scientific Investigation, Technology and Innovation (2017–2020) and cofunded by European Regional Development Fund/European Social fund 'A way to make Europe'/'Investing in your future' (grant ID PT17/0017/0013

Incidence of suspected serious adverse drug reactions in corona virus Ddsease-19 patients detected by a pharmacovigilance program by laboratory signals in a tertiary hospital in Spain: Cautionary data

BACKGROUND: From March to April 2020, Spain was the center of the SARS-CoV-2 pandemic, particularly Madrid with approximately 30% of the cases in Spain. The aim of this study is to report the suspected serious adverse drug reactions (SADRs) in COVID-19 patients vs. non-COVID-19 patients detected by the prospective pharmacovigilance program based on automatic laboratory signals (ALSs) in the hospital (PPLSH) during that period. We also compared the results with the suspected SADRs detected during the same period for 2019. METHODS: All ALSs that reflected potential SADRs including neutropenia, pancytopenia, thrombocytopenia, anemia, eosinophilia, leukocytes in cerebrospinal fluid, hepatitis, pancreatitis, acute kidney injury, rhabdomyolysis, and hyponatremia were prospectively monitored in hospitalized patients during the study periods. We analyzed the incidence and the distribution of causative drugs for the COVID-19 patients. RESULTS: The incidence rate of SADRs detected in the COVID-19 patients was 760.63 (95% CI 707.89–816.01) per 10,000 patients, 4.75-fold higher than the SADR rate for non-COVID-19 patients (160.15 per 10,000 patients, 95% CI 137.09–186.80), and 5.84-fold higher than the SADR rate detected for the same period in 2019 (130.19 per 10,000 patients, 95% CI 109.53–154.36). The most frequently related drugs were tocilizumab (59.84%), dexketoprofen (13.93%), azithromycin (8.43%), lopinavir-ritonavir (7.35%), dexamethasone (7.62%), and chloroquine/hydroxychloroquine (6.91%). CONCLUSIONS: The incidence rate of SADRs detected by the PPSLH in patients with COVID-19 was 4.75-fold higher than that of the non-COVID-19 patients. Caution is recommended when using medications for COVID-19 patients, especially drugs that are hepatotoxic, myotoxic, and those that induce thromboembolic events

Population pharmacokinetic modelling of imatinib in healthy subjects receiving a single dose of 400 mg

Purpose: Imatinib is indicated for treatment of CML, GIST, etc. The population pharmacokinetics (popPK) of imatinib in patients under long-term treatment are reported in literature. Data obtained from bioequivalence trials for healthy subjects were used to evaluate the influence of demographic and pharmacogenetic factors on imatinib pharmacokinetics (PK) in a collective without concurrent drugs, organ dysfunction, inflammation etc. In addition, the differences in PK between the healthy subjects and a patient cohort was examined to identify possible disease effects. Methods: 26 volunteers were administered orally with single dose of 400 mg imatinib. 16–19 plasma samples per volunteer were collected from 0.5 up to 72 h post-dose. The popPK was built and post hoc estimates were compared with previously published PK parameters evaluated by non-compartmental analysis in the same cohort. The predictivity of the model for data collected from 40 patients with gastrointestinal stromal tumors at steady state was evaluated. Results: The popPK was best described by a two-compartment transit model with first-order elimination. No significant covariates were identified, probably due to the small cohort and the narrow range of demographic covariates; CYP3A5 phenotypes appeared to have some influence on the clearance of imatinib. Good agreement between non-compartment and popPK analyses was observed with the differences of the geometric means/ median of PK estimates below 10%. The model indicated lower clearance for patients compared to healthy volunteers (p value < 0.01). Conclusion: The two-compartment transit model adequately describes the absorption and distribution of imatinib in healthy volunteers. For patients, a lower clearance of imatinib compared to healthy volunteer was estimated by the model. The model can be applied for dose individualization based on trough concentrations assuming no significant differences in absorption between patients and healthy volunteersThis work was part of the master these of Yi-Han Chien. There was no funding for this work. P. Zubiaur’s contract with CIBERehd is fnanced by the “Infraestructura de Medicina de Precisión asociada a la Ciencia y Tecnología (IMPaCT, IMP/00009)”, Instituto de Salud Carlos III (ISCIII

Toward a clinical practice guide in pharmacogenomics testing for functional polymorphisms of drug-metabolizing enzymes. Gene/drug pairs and barriers perceived in Spain

The development of clinica lpractice recommendations or guidelines for the clinical use of biomarkers is an issue of great importance withr regard to adverse drug reactions.The poten-tial of pharmacogenomicbiomarkers has been extensively investigated in recent years.However,several barriers to implementing the use of pharmacogenomics testing exist.We conducted a survey among members of the Spanish Societies of Pharmacology and Clinical Pharmacology to obtain information about the perception of such barriers and to compare the perceptions of participants about the relative importance of majorgene/drug pairs.Of 11 potential barriers,the highest importance was attributed to lack of institutional support for pharmacogenomic stesting,and to the issues related to the lack of guidelines.Of the proposed gene/drug pairs the highest importance was assigned to HLA-B/abacavir, UGT1A1/irinotecan, and CYP2D6/tamoxifen.In this perspective article,we compare the relative importance of 29 gene/drugpairs in the Spanish study with that of the same pairs in the American Society for Clinical Pharmacology and Therapeutic sstudy,and we provide suggestions and areas of focus to develop a guide for clinical practice in pharmacogenomics testingThe work in the author’s laboratory is financed by Grants PS09/00943, PS09/00469, RETICS RIRAAF RD07/0064/0016, and CIBERehd from Instituto de Salud CarlosIII,Madrid, Spain, and by Grants GR10068 from Junta de Extremadura, Spain. Financed in part with FEDER funds from the European Unio

Identification and validation of clinical phenotypes with prognostic implications in patients admitted to hospital with COVID-19: a multicentre cohort study

REIPI-SEIMC COVID-19 group and COVID@HULP group.[Background] The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality.[Methods] In this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model.[Findings] Three distinct phenotypes were derived in the derivation cohort (n=2667)—phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])—and reproduced in the internal validation cohort (n=1368)—phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2·5% (95% CI 1·4–4·3) for patients with phenotype A, 30·5% (28·5–32·6) for patients with phenotype B, and 60·7% (53·7–67·2) for patients with phenotype C (log-rank test p<0·0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5·3% [95% CI 3·4–8·1] for phenotype A, 31·3% [28·5–34·2] for phenotype B, and 59·5% [48·8–69·3] for phenotype C; external validation cohort: 3·7% [2·0–6·4] for phenotype A, 23·7% [21·8–25·7] for phenotype B, and 51·4% [41·9–60·7] for phenotype C).[Interpretation] Patients admitted to hospital with COVID-19 can be classified into three phenotypes that correlate with mortality. We developed and validated a simplified tool for the probabilistic assignment of patients into phenotypes. These results might help to better classify patients for clinical management, but the pathophysiological mechanisms of the phenotypes must be investigated.[Funding] Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Fundación SEIMC/GeSIDA.Funding: Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Fundación SEIMC/GeSIDA.Peer reviewe

Consensus of experts from the Spanish pharmacogenetics and pharmacogenomics society and the Spanish society of medical oncology for the genotyping of DPYD in cancer patients who are candidates for treatment with fluoropyrimidines

5-Fluorouracil (5-FU) and oral fluoropyrimidines, such as capecitabine, are widely used in the treatment of cancer, especially gastrointestinal tumors and breast cancer, but their administration can produce serious and even lethal toxicity. This toxicity is often related to the partial or complete deficiency of the dihydropyrimidine dehydrogenase (DPD) enzyme, which causes a reduction in clearance and a longer half-life of 5-FU. It is advisable to determine if a DPD deficiency exists before administering these drugs by genotyping DPYD gene polymorphisms. The objective of this consensus of experts, in which representatives from the Spanish Pharmacogenetics and Pharmacogenomics Society and the Spanish Society of Medical Oncology participated, is to establish clear recommendations for the implementation of genotype and/or phenotype testing for DPD deficiency in patients who are candidates to receive fluoropyrimidines. The genotyping of DPYD previous to treatment classifies individuals as normal, intermediate, or poor metabolizers. Normal metabolizers do not require changes in the initial dose, intermediate metabolizers should start treatment with fluoropyrimidines at doses reduced to 50%, and poor metabolizers are contraindicated for fluoropyrimidinesThis project has been financed with SEOM and SEFF resource

A cohort of patients with COVID-19 in a major teaching hospital in Europe

Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración, si le hubiere, y los autores pertenecientes a la UAMArtículo escrito en nombre del COVID@HULP Working GroupSince the confirmation of the first patient infected with SARS-CoV-2 in Spain in January 2020, the epidemic has grown rapidly, with the greatest impact on the region of Madrid. This article describes the first 2226 adult patients with COVID-19, consecutively admitted to La Paz University Hospital in Madrid. Methods: Our cohort included all patients consecutively hospitalized who had a final outcome (death or discharge) in a 1286-bed hospital of Madrid (Spain) from 25 February (first case admitted) to 19 April 2020. The data were manually entered into an electronic case report form, which was monitored prior to the analysis. Results: We consecutively included 2226 adult patients admitted to the hospital who either died (460) or were discharged (1766). The patients’ median age was 61 years, and 51.8% were women. The most common comorbidity was arterial hypertension (41.3%), and the most common symptom on admission was fever (71.2%). The median time from disease onset to hospital admission was 6 days. The overall mortality was 20.7% and was higher in men (26.6% vs. 15.1%). Seventy-five patients with a final outcome were transferred to the intensive care unit (ICU) (3.4%). Most patients admitted to the ICU were men, and the median age was 64 years. Baseline laboratory values on admission were consistent with an impaired immune-inflammatory profile. Conclusions: We provide a description of the first large cohort of hospitalized patients with COVID-19 in Europe. Advanced age, male sex, the presence of comorbidities and abnormal laboratory values were more common among the patients with fatal outcome

A new pharmacogenetic algorithm to predict the most appropriate dosage of acenocoumarol for stable anticoagulation in a mixed Spanish population

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9∗2 (rs1799853), CYP2C9∗3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R2) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (&lt;11 mg/week, 11-21 mg/week, &gt;21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases.This study was funded by a grant from the Spanish Ministry of Health and Social Policy (Instituto de Salud Carlos III, PI07/0710) and the Andalusian Regional Ministry of Health (Progress and Health Foundation, PI-0717-2013