Randomized Placebo-Controlled Trial Evaluating the Ophthalmic Safety of Single-Dose Tafenoquine in Healthy Volunteers Abstract Introduction Tafenoquine has been recently registered for the prevention of relapse in Plasmodium vivax malaria. Objective This study assessed the pharmacodynamic effects of 300-mg single-dose tafenoquine on the retina. Methods This phase I, prospective, multicenter, randomized, single-masked, placebo-controlled, parallel-group study was conducted between 2 February 2016 and 14 September 2017 at three US study centers. Adult healthy volunteers were randomized (2:1) to receive either a single 300-mg oral dose of tafenoquine or matched placebo on day 1. Ophthalmic assessments, including spectral domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF), were conducted at baseline and day 90 and evaluated for pre-determined endpoints by an independent, masked reading center. Results One subject in each group met the composite primary endpoint for retinal changes identified with SD-OCT or FAF, i.e., one out of 306 (0.3%) with tafenoquine, one out of 161 (0.6%) with placebo. Both cases had unilateral focal ellipsoid zone disruption at day 90 with no effect on best-corrected visual acuity. The tafenoquine-treated subject had this abnormality at baseline, and was enrolled in error. There was no difference in ophthalmic safety between tafenoquine and placebo. Conclusion There was no evidence of any pharmacodynamic effect of 300-mg single-dose tafenoquine on the retina or any short-term clinically relevant effects on ophthalmic safety. This clinical trial is registered with ClinicalTrials.gov (identifier: NCT02658435).

Antidepressants and the Risk of Hemorrhagic Stroke in the Elderly: a Nested Case–Control Study Abstract Background and Purpose Selective serotonin reuptake inhibitors (SSRIs) are frequently prescribed in the elderly due to a more favorable risk profile than other antidepressants (ADs). However, SSRIs are associated with an increased risk of gastrointestinal bleeding, while evidence on the risk of hemorrhagic stroke (HS) is limited. Therefore, we compared the risk of HS associated with the use of ADs in the elderly. Methods Based on data from the German Pharmacoepidemiological Research Database (GePaRD), a case–control study matched on age, sex, and health insurance provider, nested in a cohort of incident users of ADs ≥ 65 years of age was performed. Cases were identified from hospital discharge diagnoses, and exposure was identified from outpatient prescriptions. Multivariable conditional logistic regression was used to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Results Based on 4059 cases and 40,590 controls, an increased risk of HS was found in current use of SSRIs (OR 1.39, 95% CI 1.22–1.58), selective serotonin and noradrenaline reuptake inhibitors (1.69, 1.35–2.11), noradrenergic and specific serotonergic ADs (1.44, 1.22–1.69), and noradrenaline reuptake inhibitors (3.81, 1.54–9.43) compared with tri- and tetracyclic antidepressants. An increased risk of HS was seen in patients with a high baseline risk of bleeding and in patients with depression. The risk of HS varied between individual ADs. Conclusion Our study shows that the use of medications inhibiting serotonin and/or noradrenaline reuptake increases the risk of HS in patients aged 65 years and older and that the risk varies across individual ADs.

Prevalence, Safety and Long-Term Retention Rates of Biologics in Hong Kong from 2001 to 2015 Abstract Background Biologic agents were initially introduced as treatment for rheumatoid arthritis (RA) but have since been used for other medical conditions. As new biologics become increasingly widespread in treatment regimens, it is important to understand their safety and utilization in the post-marketing context. Purpose The aim of this study was to investigate long-term prescribing patterns and the safety of biologics in real clinical settings in Hong Kong. Methods This was a population-based drug utilization study in Hong Kong using a territory-wide electronic medical database Clinical Data Analysis and Reporting System (CDARS). Patients who received biologic treatments from 2001 to 2015 were identified and their corresponding demographic and clinical details retrieved from CDARS. The annual prevalence of biologic prescriptions, the long-term retention rates and incidence rates of infections associated with biologic treatments were evaluated. Results A total of 30,298 patients (male: 44%) prescribed biologic treatments were identified from CDARS from 2001 to 2015. The annual prevalence of biologic prescriptions increased from 0.1 to 16.1 per 100 persons for both sexes. Infliximab had the highest first-year retention rate of 95.6% among all biologics and continuously attained the highest retention rate from second to fifth year. The overall incidence rate of serious infections was less than five per 100 person-years. Specifically, the incidence rates of tuberculosis, upper and lower respiratory infections and herpes zoster were 0.52, 3.24, 4.99 and 1.01 per 100 person-years, respectively. Conclusion This population-based study revealed an increasing prevalence of biologic prescribing. Results from the study described the long-term retention rates and incidence rates of serious infections of biologic treatments for all indications, and confirmed the safety of biologic treatments. Since this study provides an overview of all biologic utilization, further studies on cost effectiveness, safety and compliance of treatment in different patient groups are still warranted.

Fluoroquinolone Use and the Risk of Collagen-Associated Adverse Events: A Systematic Review and Meta-Analysis Abstract Introduction It has been suggested that fluoroquinolone antibiotics increase the risk of developing collagen-associated adverse events such as aortic dissection and aortic aneurysm. These are life-threatening emergencies that need to be prevented. Objectives We performed this systematic review to clarify the association between fluoroquinolones and three collagen-associated adverse events: aortic aneurysm or aortic dissection, retinal detachment, and tendon disorders. Methods We searched PubMed, Embase, and Scopus for observational studies up to January 2019. Cohort and case–control studies were included if they reported data on the risk of collagen-related adverse events associated with fluoroquinolone exposure versus no exposure. We assessed the quality of the included studies using the Newcastle–Ottawa Scale. Effect statistics were pooled using random-effects models. Sensitivity and subgroup analyses were performed to identify any source of heterogeneity. Results After screening 2729 citations, we included 22 observational studies (12 cohort studies and ten case–control studies) with 19,207,552 participants. Current use of fluoroquinolones was significantly associated with aortic aneurysm and aortic dissection (odds ratio [OR] 2.20; 95% confidence interval [CI] 1.92–2.52), tendon disorders (OR 1.89; 95% CI 1.53–2.33), and retinal detachment (sensitivity analysis, OR 1.25; 95% CI 1.01–1.53). Past fluoroquinolone use (> 30 and ≤ 365 days) was associated with retinal detachment (OR 1.27; 95% CI 1.09–1.47). Conclusions Fluoroquinolone use incurs a risk of developing three collagen-associated diseases (aortic aneurysm or aortic dissection, retinal detachment, and tendon disorders). Patients at an increased risk of collagen-associated diseases should not use fluoroquinolones unless no other options are available.

Auto-Generated Physiological Chain Data for an Ontological Framework for Pharmacology and Mechanism of Action to Determine Suspected Drugs in Cases of Dysuria Abstract Introduction Patients often take several different medications for multiple conditions concurrently. Therefore, when adverse drug events (ADEs) occur, it is necessary to consider the mechanisms responsible. Few approaches consider the mechanisms of ADEs, such as changes in physiological states. We proposed that the ontological framework for pharmacology and mechanism of action (pharmacodynamics) we developed could be used for this approach. However, the existing knowledge base contains little data on physiological chains (PCs). Objective We aimed to investigate a method for automatically generating missing PC from the viewpoint of anatomical structures. This study was conducted to determine dysuria-related adverse events more likely to occur during multidrug administration. Methods We adopted a systematic approach to determine drugs suspected to cause adverse events and incorporated existing data and data generated in our newly developed method into our ontological framework. The performance of automated data generation was evaluated using this newly developed system. Suspected drugs determined by the system were compared with those derived from adverse events databases. Results Of the 242 drugs involving suspected drug-induced urinary retention or dysuria, 26 suspected drugs were determined. Of these, five were drugs with side effects not listed in drug package inserts. The system derived potential mechanisms of action, PCs, and suspected drugs. Conclusion Our method is novel in that it generates PC data from anatomical structural properties and could serve as a knowledge base for determining suspected drugs by potential mechanisms of action.

Evaluation of Use of Technologies to Facilitate Medical Chart Review Abstract Introduction While medical chart review remains the gold standard to validate health conditions or events identified in administrative claims and electronic health record databases, it is time consuming, expensive and can involve subjective decisions. Aim The aim of this study was to describe the landscape of technology-enhanced approaches that could be used to facilitate medical chart review within and across distributed data networks. Method We conducted a semi-structured survey regarding processes for medical chart review with organizations that either routinely do medical chart review or use technologies that could facilitate chart review. Results Fifteen out of 17 interviewed organizations used optical character recognition (OCR) or natural language processing (NLP) in their chart review process. None used handwriting recognition software. While these organizations found OCR and NLP to be useful for expediting extraction of useful information from medical charts, they also mentioned several challenges. Quality of medical scans can be variable, interfering with the accuracy of OCR. Additionally, linguistic complexity in medical notes and heterogeneity in reporting templates used by different healthcare systems can reduce the transportability of NLP-based algorithms to diverse healthcare settings. Conclusion New technologies including OCR and NLP are currently in use by various organizations involved in medical chart review. While technology-enhanced approaches could scale up capacity to validate key variables and make information about important clinical variables from medical records more generally available for research purposes, they often require considerable customization when employed in a distributed data environment with multiple, diverse healthcare settings.

Evaluation of Potential Drug–Drug Interactions in Adults in the Intensive Care Unit: A Systematic Review and Meta-Analysis Abstract Introduction There is an increased risk of potential drug–drug interactions (pDDIs) in critically ill patients based on the number of drugs received. The occurrence of pDDIs and clinical significance is not well described. Objective The aim was to provide insight into important clinical issues and offer guidance on drug–drug interaction (DDI) surveillance through the performance of a systematic review. Methods Five targeted objectives were developed, a priori, which guided study selection and data abstraction. Two independent reviewers extracted the definition, frequency, type, and clinical significance of pDDIs. A meta-analysis was performed to evaluate the proportion of patients exposed to a pDDI. Three data sources (PubMed, Embase, and Scopus) were utilized for the search to include studies that evaluated pDDIs in adult critically ill patients. Included studies in the systematic review and meta-analysis were required to be full text. Results A total of 39 studies met inclusion criteria. Definitions of pDDIs were diverse. Frequency of pDDIs varied by study, but was most commonly between one and five pDDIs per patient. Fifty-eight percent of patients were exposed to at least one pDDI during their intensive care unit admission. Types of pDDIs identified were numerous, with aspirin being the most common drug involved. As expected, not all pDDIs were clinically significant. Clinical significance was determined by varied definitions and sources. Conclusions Improving the understanding of clinically significant pDDIs and alerts that clinicians encounter may guide better development of surveillance through clinical decision support and decrease alert fatigue.

Enabling Data-Driven Clinical Quality Assurance: Predicting Adverse Event Reporting in Clinical Trials Using Machine Learning Abstract Introduction Adverse event (AE) under-reporting has been a recurrent issue raised during health authorities Good Clinical Practices (GCP) inspections and audits. Moreover, safety under-reporting poses a risk to patient safety and data integrity. The current clinical Quality Assurance (QA) practices used to detect AE under-reporting rely heavily on investigator site and study audits. Yet several sponsors and institutions have had repeated findings related to safety reporting, and this has led to delays in regulatory submissions. Recent developments in data management and IT systems allow data scientists to apply techniques such as machine learning to detect AE under-reporting in an automated fashion. Objective In this project, we developed a predictive model that enables Roche/Genentech Quality Program Leads oversight of AE reporting at the program, study, site, and patient level. This project was part of a broader effort at Roche/Genentech Product Development Quality to apply advanced analytics to augment and complement traditional clinical QA approaches. Method We used a curated data set from 104 completed Roche/Genentech sponsored clinical studies to train a machine learning model to predict the expected number of AEs. Our final model used 54 features built on patient (e.g., demographics, vitals) and study attributes (e.g., molecule class, disease area). Results In order to evaluate model performance, we tested how well it would detect simulated test cases based on data not used for model training. For relevant simulation scenarios of 25%, 50%, and 75% under-reporting on the site level, our model scored an area under the curve (AUC) of the receiver operating characteristic (ROC) curve of 0.62, 0.79, and 0.92, respectively. Conclusion The model has been deployed to evaluate safety reporting performance in a set of ongoing studies in the form of a QA/dashboard cockpit available to Roche Quality Program Leads. Applicability and production performance will be assessed over the next 12–24 months in which we will develop a validation strategy to fully integrate our model into Roche QA processes.

Prevalence and Nature of Medication Errors and Preventable Adverse Drug Events in Paediatric and Neonatal Intensive Care Settings: A Systematic Review Abstract Introduction Children admitted to paediatric and neonatal intensive care units may be at high risk from medication errors and preventable adverse drug events. Objective The objective of this systematic review was to review empirical studies examining the prevalence and nature of medication errors and preventable adverse drug events in paediatric and neonatal intensive care units. Data Sources Seven electronic databases were searched between January 2000 and March 2019. Study Selection Quantitative studies that examined medication errors/preventable adverse drug events using direct observation, medication chart review, or a mixture of methods in children ≤ 18 years of age admitted to paediatric or neonatal intensive care units were included. Data Extraction Data on study design, detection method used, rates and types of medication errors/preventable adverse drug events, and medication classes involved were extracted. Results Thirty-five unique studies were identified for inclusion. In paediatric intensive care units, the median rate of medication errors was 14.6 per 100 medication orders (interquartile range 5.7–48.8%, n = 3) and between 6.4 and 9.1 per 1000 patient-days (n = 2). In neonatal intensive care units, medication error rates ranged from 4 to 35.1 per 1000 patient-days (n = 2) and from 5.5 to 77.9 per 100 medication orders (n = 2). In both settings, prescribing and medication administration errors were found to be the most common medication errors, with dosing errors the most frequently reported error subtype. Preventable adverse drug event rates were reported in three paediatric intensive care unit studies as 2.3 per 100 patients (n = 1) and 21–29 per 1000 patient-days (n = 2). In neonatal intensive care units, preventable adverse drug event rates from three studies were 0.86 per 1000 doses (n = 1) and 0.47–14.38 per 1000 patient-days (n = 2). Anti-infective agents were commonly involved with medication errors/preventable adverse drug events in both settings. Conclusions Medication errors occur frequently in critically ill children admitted to paediatric and neonatal intensive care units and may lead to patient harm. Important targets such as dosing errors and anti-infective medications were identified to guide the development of remedial interventions.

Established and Emerging Immunological Complications of Biological Therapeutics in Multiple Sclerosis Abstract Biologic immunotherapies have transformed the treatment landscape of multiple sclerosis. Such therapies include recombinant proteins (interferon beta), as well as monoclonal antibodies (natalizumab, alemtuzumab, daclizumab, rituximab and ocrelizumab). Monoclonal antibodies show particular efficacy in the treatment of the inflammatory phase of multiple sclerosis. However, the immunological perturbations caused by biologic therapies are associated with significant immunological adverse reactions. These include development of neutralising immunogenicity, secondary immunodeficiency and secondary autoimmunity. These complications can affect the balance of risks and benefits of biologic agents, and 2018 saw the withdrawal from the market of daclizumab, an anti-CD25 monoclonal antibody, due to concerns about the development of severe, unpredictable autoimmunity. Here we review established and emerging risks associated with multiple sclerosis biologic agents, with an emphasis on their immunological adverse effects. We also discuss the specific challenges that multiple sclerosis biologics pose to drug safety systems, and the potential for improvements in safety frameworks.