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Longitudinal electronic healthcare data hold great potential for drug safety surveillance. The tree-based scan statistic (TBSS), as implemented by the TreeScan® software, allows for hypothesis-free signal detection in longitudinal data by grouping safety events according to branching, hierarchical data coding systems, and then identifying signals of disproportionate recording (SDRs) among the singular events or event groups. The objective of this analysis was to identify and visualize SDRs with the TBSS in historical data from patients using two antifungal drugs, itraconazole or terbinafine. By examining patients who used either itraconazole or terbinafine, we provide a conceptual replication of a previous TBSS analyses by varying methodological choices and using a data source that had not been previously used with the TBSS, i.e., the Optum Clinformatics™ claims database. With this analysis, we aimed to test a parsimonious design that could be the basis of a broadly applicable method for multiple drug and safety event pairs. The TBSS analysis was used to examine incident events and any itraconazole or terbinafine use among US-based patients from 2002 through 2007. Event frequencies before and after the first day of drug exposure were compared over 14- and 56-day periods of observation in a Bernoulli model with a self-controlled design. Safety events were classified into a hierarchical tree structure using the Clinical Classifications Software (CCS) which mapped International Classification of Diseases, 9th Revision (ICD-9) codes to 879 diagnostic groups. Using the TBSS, the log likelihood ratio of observed versus expected events in all groups along the CCS hierarchy were compared, and groups of events that occurred at disproportionally high frequencies were identified as potential SDRs; p-values for the potential SDRs were estimated with Monte-Carlo permutation based methods. Output from TreeScan® was visualized and plotted as a network which followed the CCS tree structure. Terbinafine use (n = 223,968) was associated with SDRs for diseases of the circulatory system (14- and 56-day p = 0.001) and heart (14-day p = 0.026 and 56-day p = 0.001) as well as coronary atherosclerosis and other heart disease (14-day p = 0.003 and 56-day p = 0.004). For itraconazole use (n = 36,025), the TBSS identified SDRs for coronary atherosclerosis and other heart disease (p = 0.002) and complications of an implanted or grafted device (14-day p = 0.001 and 56-day p

Introduction Cohort event monitoring (CEM) is an intensive method of post-marketing surveillance for medicines safety. The method is based on prescription event monitoring, which began in the 1970s, and has since been adapted by WHO for monitoring the safety of medicines used in Public Health Programmes. CEM aims to capture all adverse events that occur in a defined group of patients after starting treatment with a specific medicine during the course of routine clinical practice. Objective The aims of this study were to describe the experiences of National Pharmacovigilance Centres (NCs) that have used CEM to monitor artemisinin-based combination therapy (ACT) for uncomplicated malaria in the African setting, to raise awareness of some of the challenges encountered during implementation and to highlight aspects of the method that require further consideration. Method A questionnaire-based survey was conducted to capture the experiences of NCs that have implemented CEM for active post-marketing surveillance of antimalarial medicines in sub-Saharan Africa. Six NCs were identified as having implemented CEM programmes and were invited to participate in the survey; five NCs indicated willingness to participate and were sent the questionnaire to complete. Results Four NCs responded to the survey—Ghana, Kenya, Nigeria and Zimbabwe—providing information on the implementation of a total of six CEM programmes. Their experiences indicate that CEM has helped to build pharmacovigilance capacity within the participating NCs and at the monitoring sites, and that healthcare providers (HCPs) are generally willing to participate in implementing the CEM method. All of the programmes took longer than expected to complete: contributing factors included a prolonged enrolment period and unexpectedly slow data entry. All of the programmes exceeded their budget by 11.1–63.2 %. Data management was identified as a challenge for all participating NCs. Conclusions The reported experiences of four NCs that have undertaken CEM studies on ACTs indicate that CEM has helped to build pharmacovigilance capacity within NCs and monitoring sites and that HCPs are willing to participate in CEM programmes; however, the method was found to be labour intensive and data management was identified as a challenge. Reducing the workload associated with CEM, particularly in relation to data management, and integrating the method into the routine work of HCPs and NCs should be considered for future implementation. Electronic supplementary material The online version of this article (doi:10.1007/s40264-015-0331-7) contains supplementary material, which is available to authorized users.

BackgroundAntimalarial treatment strategies have changed much in the last 15 years, resulting in an increased variety of medicines available. Active pharmacovigilance methods are important for continued safety surveillance of these medicines, particularly in environments in which there is variability in treatments prescribed and limited confirmatory diagnostic capacity as well as limited ability of spontaneous reporting pharmacovigilance systems to generate much needed safety information quickly and efficiently.ObjectiveOur objective was to use the cohort-event monitoring (CEM) technique to gather drug utilization and adverse event data for patients prescribed antimalarial medicines in an outpatient setting.MethodsThe characteristics of a large urban African cohort of outpatients (n = 2,831) receiving antimalarial medications are described. The cohort was actively surveyed over the subsequent week to record adverse events, using follow-up phone calls, paper reports, and/or voluntary return clinic visits. Adverse events reported in the cohort were analysed overall and by clinically relevant age and medication groupings.ResultsAt least one event was reported in 29.4 % of patients. Adverse events were more likely to be reported in subjects older than 12 years of age, and by patients prescribed an artesunate-amodiaquine combination. A range of adverse events were reported, the most frequent higher level terms being asthenic conditions (10.1 % of total cohort), neurological signs and symptoms (4.5 %), headaches (3.1 %), appetite disorders (2.1 %), and disturbances in consciousness (1.6 %). There were three reports of possible extrapyramidal events (two cases of tremor “hand and back shaking all over” and one case of tongue protrusion), which may appear to be related to combinations including amodiaquine and an artemisinin.ConclusionThe CEM methodology is a useful tool for monitoring the safety of widely available and utilized medicines, particularly in an urban environment where spontaneous reporting yields poor results and where the availability of various regimens and high levels of medicine usage can give valuable ‘real-life’ safety data. The types and frequencies of events reported reflected the types of events expected in patients prescribed antimalarials and nearly all events reported are listed in the summary of product characteristics of the medicines involved.

Globally, national pharmacovigilance systems rely on spontaneous reporting in which suspected adverse drug reactions (ADRs) are reported to a national coordinating centre by health professionals, manufacturers or patients. Spontaneous reporting systems are the easiest to establish and the cheapest to run but suffer from poor-quality reports and underreporting. It is difficult to estimate rates and frequencies of ADRs through spontaneous reporting. Public health programmes need to quantify and characterize risks to individuals and communities from their medicines, to minimize harm and improve use, to sustain public confidence in the programmes, and to track problems due to medication errors and poor quality medicines. Additional methods are therefore needed to monitor the quantitative aspects of medicine safety, to better identify specific risk factors and high-risk groups, and to characterize ADRs associated with specific medicines and in specific populations. The present paper introduces two methods, cohort event monitoring and targeted spontaneous reporting, that are being implemented by the WHO, in its public health programmes, to complement spontaneous reporting. The advantages and disadvantages of these methods and how each can be applied in clinical practice are discussed.