Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study

Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research

Diagnosis of Chronic Pulmonary Aspergillosis: Clinical, Radiological or Laboratory?

Chronic pulmonary aspergillosis (CPA) is a chronic progressive lung disease associated with a poor prognosis and a 5-year mortality rate of approximately 40–50%. The disease is characterized by slowly progressive destruction of the lung parenchyma, in the form of multiple cavities, nodules, infiltrates or fibrosis. CPA can be challenging to diagnose due to its non-specific symptoms and similarities with other respiratory conditions combined with the poor awareness of the medical community about the disease. This can result in delayed treatment even for years and worsening of the patient’s condition. Serological tests certainly play a significant role in diagnosing CPA but cannot be interpreted without radiological confirmation of CPA. Although many data are published on this hot topic, there is yet no single definitive test for diagnosing CPA, and a multidisciplinary approach which involves a combination of clinical picture, radiological findings, microbiological results and exclusion of other mimicking diseases, is essential for the accurate diagnosis of CPA

Gut-Liver Axis, Gut Microbiota, and Its Modulation in the Management of Liver Diseases: A Review of the Literature

The rapid scientific interest in gut microbiota (GM) has coincided with a global increase in the prevalence of infectious and non-infectivous liver diseases. GM, which is also called “the new virtual metabolic organ”, makes axis with a number of extraintestinal organs, such as kidneys, brain, cardiovascular, and the bone system. The gut-liver axis has attracted greater attention in recent years. GM communication is bi-directional and involves endocrine and immunological mechanisms. In this way, gut-dysbiosis and composition of “ancient” microbiota could be linked to pathogenesis of numerous chronic liver diseases such as chronic hepatitis B (CHB), chronic hepatitis C (CHC), alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), development of liver cirrhosis, and hepatocellular carcinoma (HCC). In this paper, we discuss the current evidence supporting a GM role in the management of different chronic liver diseases and potential new therapeutic GM targets, like fecal transplantation, antibiotics, probiotics, prebiotics, and symbiotics. We conclude that population-level shifts in GM could play a regulatory role in the gut-liver axis and, consequently, etiopathogenesis of chronic liver diseases. This could have a positive impact on future therapeutic strategies