Paediatric safety signals identified in VigiBase: Methods and results from Uppsala Monitoring Centre.

PURPOSE: The purpose of this study is to uncover previously unrecognised risks of medicines in paediatric pharmacovigilance reports and thereby advance a safer use of medicines in paediatrics. METHODS: Individual case safety reports (ICSRs) with ages less than 18 years were retrieved from VigiBase, the World Health Organization (WHO) global database of ICSRs, in September 2014. The reports were grouped according to the following age spans: 0 to 27 days; 28 days to 23 months; 2 to 11 years; and 12 to 17 years. vigiRank, a data-driven predictive model for emerging safety signals, was used to prioritise the list of drug events by age groups. The list was manually assessed, and potential signals were identified to undergo in-depth assessment to determine whether a signal should be communicated. RESULTS: A total of 472 drug-event pairs by paediatric age groups were the subject of an initial manual assessment. Twenty-seven drug events from the two older age groups were classified as potential signals. An in-depth assessment resulted in eight signals, of which one concerned harm in connection with off-label use of dextromethorphan and another with accidental overdose of olanzapine by young children, and the remaining signals referred to potentially new causal associations for atomoxetine (two signals), temozolamide, deferasirox, levetiracetam, and desloratadine that could be relevant also for adults. CONCLUSIONS: Clinically relevant signals were uncovered in VigiBase by using vigiRank applied to paediatric age groups. Further refinement of the methodology is needed to identify signals in reports with ages under 2 years and to capture signals specific to the paediatric population as a risk group.

Quantitative benefit-risk assessment of methylprednisolone in multiple sclerosis relapses.

BACKGROUND: High-dose short-term methylprednisolone is the recommended treatment in the management of multiple sclerosis relapses, although it has been suggested that lower doses may be equally effective. Also, glucocorticoids are associated with multiple and often dose-dependent adverse effects. This quantitative benefit-risk assessment compares high- and low-dose methylprednisolone (at least 2000 mg and less than 1000 mg, respectively, during at most 31 days) and a no treatment alternative, with the aim of determining which regimen, if any, is preferable in multiple sclerosis relapses. METHODS: An overall framework of probabilistic decision analysis was applied, combining data from different sources. Effectiveness as well as risk of non-serious adverse effects were estimated from published clinical trials. However, as these trials recorded very few serious adverse effects, risk intervals for the latter were derived from individual case reports together with a range of plausible distributions. Probabilistic modelling driven by logically implied or clinically well motivated qualitative relations was used to derive utility distributions. RESULTS: Low-dose methylprednisolone was not a supported option in this assessment; there was, however, only limited data available for this treatment alternative. High-dose methylprednisolone and the no treatment alternative interchanged as most preferred, contingent on the risk distributions applied for serious adverse effects, the assumed level of risk aversiveness in the patient population, and the relapse severity. CONCLUSIONS: The data presently available do not support a change of current treatment recommendations. There are strong incentives for further clinical research to reduce the uncertainty surrounding the effectiveness and the risks associated with methylprednisolone in multiple sclerosis relapses; this would enable better informed and more precise treatment recommendations in the future.

Longitudinal medical records as a complement to routine drug safety signal analysis.

PURPOSE: To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database. METHODS: Drug and ADR combinations from the routine signal detection process of VigiBase® in 2011 were matched to combinations in The Health Improvement Network (THIN). The number and type of drugs and ADRs from the data sets were investigated. For unlabelled combinations, graphical display of longitudinal event patterns (chronographs) in THIN was inspected to determine if the pattern supported the VigiBase combination. RESULTS: Of 458 combinations in the VigiBase data set, 190 matched to corresponding combinations in THIN (after excluding drugs with less than 100 prescriptions in THIN). Eighteen percent of the VigiBase and 9% of the matched THIN combinations referred to new drugs reported with serious reactions. Of the 112 unlabelled combinations matched to THIN, 52 chronographs were inconclusive mainly because of lack of data; 34 lacked any outstanding pattern around the time of prescription; 24 had an elevation of events in the pre-prescription period, hence weakened the suspicion of a drug relationship; two had an elevated pattern of events exclusively in the post-prescription period that, after review of individual patient histories, did not support an association. CONCLUSIONS: Longitudinal medical records were useful in understanding the clinical context around a drug and suspected ADR combination and the probability of a causal relationship. A drawback was the paucity of data for newly marketed drugs with serious reactions.

Computing limits on medicine risks based on collections of individual case reports.

BACKGROUND: Quantifying a medicine's risks for adverse effects is crucial in assessing its value as a therapeutic agent. Rare adverse effects are often not detected until after the medicine is marketed and used in large and heterogeneous patient populations, and risk quantification is even more difficult. While individual case reports of suspected harm from medicines are instrumental in the detection of previously unknown adverse effects, they are currently not used for risk quantification. The aim of this article is to demonstrate how and when limits on medicine risks can be computed from collections of individual case reports. METHODS: We propose a model where drug exposures in the real world may be followed by adverse episodes, each containing one or several adverse effects. Any adverse episode can be reported at most once, and each report corresponds to a single adverse episode. Based on this model, we derive upper and lower limits for the per-exposure risk of an adverse effect for a given drug. RESULTS: An upper limit for the per-exposure risk of the adverse effect Y for a given drug X is provided by the reporting ratio of X together with Y relative to all reports on X, under two assumptions: (i) the average number of adverse episodes following exposure to X is one or less; and (ii) adverse episodes that follow X and contain Y are more frequently reported than adverse episodes in general that follow X. Further, a lower risk limit is provided by dividing the number of reports on X together with Y by the total number of exposures to X, under the assumption that exposures to X that are followed by Y generate on average at most one report on X together with Y. Using real data, limits for the narcolepsy risk following Pandemrix vaccination and the risk of coeliac disease following antihypertensive treatment were computed and found to conform to reference risk values from epidemiological studies. CONCLUSIONS: Our framework enables quantification of medicine risks in situations where this is otherwise difficult or impossible. It has wide applicability, but should be particularly useful in structured benefit-risk assessments that include rare adverse effects.

Challenges of safe medication practice in paediatric care--a nursing perspective.

AIM: To explore nurses' experiences of handling medications in paediatric clinical practice, with a focus on factors that hinder and facilitate safe medication practices. METHODS: Twenty nurses (registered nurses) from four paediatric wards at two hospitals in Sweden were interviewed in focus groups. The interviews were analysed using content analysis. RESULTS: Six themes emerged from the analysed interviews: the complexity specific for nurses working on paediatric wards is a hindrance to safe medication practices; nurses' concerns about medication errors cause a considerable psychological burden; the individual nurse works hard for safe medication practices and values support from other nurse colleagues; circumstances out of the ordinary are perceived as critical challenges for maintaining patient safety; nurses value clear instructions, guidelines and routines, but these are often missing, variable or changeable; management, other medical professionals, the pharmacy, the pharmaceutical industry and informatics support need to respond to the requirements of the nurses' working situations to improve safe medication practices. CONCLUSION: Weaknesses were apparent in the long chain of the medication-delivery process. A joint effort by different professions involved in that delivery process, and a nationwide collaboration between hospitals is recommended to increase safe medication practices in paediatric care.

Pharmacovigilance.

Adverse drug reactions are the fifth most frequent cause of deaths in developed countries, effectively a global epidemic. However, progress in ameliorating the problem has been slow. Pharmacovigilance currently operates without clear objectives in relation to individual decisions, with no protocol (although risk management plans are a great step forward), with obscure materials and methods used for making decisions, with very limited reasoning and discussion, and little or no follow up and audit of the results. Problems include under-reporting, poor quality reports, underuse of the latest communications technology and suboptimal individual feedback to reporters. Assessment of causality is poor, impeding decision-making. After signal detection, more active measures to assess the risk to public health are needed. Other essential factors include precision about the ways in which data are prepared and transformed into databases, the recognition of secondary effects, which may be more obvious than the primary effect, but not so easy to link causally, and cognisance of all kinds of interactions. Areas that should be developed include pharmacoepidemiology, knowledge finding (through data mining), and communication and systems technology. The general way forward seems clear: a rigorous way of documenting all the steps, from getting reports of harms into regulatory databases to assessing their effects on public health, is essential and should be publicly reviewed for weaknesses. In turn, matters would be much improved by input on benefit/harm perceptions from patient groups, influencing decisions about what should be the true targets for regulatory and pharmacovigilance activities, avoiding second guessing by regulators.

Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction.

AIMS: In a systematic screening of the World Health Organization Adverse Drug Reaction database, VigiBase, in July 2008, a measure of association used to detect interactions (Omega) highlighted azithromycin with the individual statins atorvastatin, lovastatin and simvastatin and rhabdomyolysis. The aim was to examine all reports including rhabdomyolysis-azithromycin and statins in VigiBase to assess if the data were suggestive of an interaction. METHODS: The individual case reports in VigiBase and the original files were reviewed. In order to investigate the reporting over time for rhabdomyolysis with azithromycin and statins to VigiBase, Omega values were generated retrospectively. RESULTS: The reporting over time showed that rhabdomyolysis under concomitant use of azithromycin and statins was reported more often than expected from 2000 and onwards in Vigibase. After exclusion of possible duplicates and follow-up reports, 53 cases from five countries remained. Rhabdomyolysis occurred shortly after initiation of azithromycin in 23% of cases. In 11 patients an interaction had been suggested by the reporter. With the exception of one patient, the statin doses reported were within the recommended daily doses. CONCLUSIONS: Case reports in VigiBase are suggestive that interactions between azithromycin and statins resulting in rhabdomyolysis may occur. This analysis showed the potential of the newly developed disproportionality measure, Omega, which can help to identify drug interactions in VigiBase in the future. The results also showed that reviewing spontaneous reports can add information to drug interactions not established previously.

Impact of stratification on adverse drug reaction surveillance.

BACKGROUND AND OBJECTIVES: Automated screening for excessive adverse drug reaction (ADR) reporting rates has proven useful as a tool to direct clinical review in large-scale drug safety signal detection. Some measures of disproportionality can be adjusted to eliminate any undue influence on the ADR reporting rate of covariates, such as patient age or country of origin, by using a weighted average of stratum-specific measures of disproportionality. Arguments have been made in favour of routine adjustment for a set of common potential confounders using stratification. The aim of this paper is to investigate the impact of using adjusted observed-to-expected ratios, as implemented for the Empirical Bayes Geometric Mean (EBGM) and the information component (IC) measures of disproportionality, for first-pass analysis of the WHO database. METHODS: A simulation study was carried out to investigate the impact of simultaneous adjustment for several potential confounders based on stratification. Comparison between crude and adjusted observed-to-expected ratios were made based on random allocation of reports to a set of strata with a realistic distribution of stratum sizes. In a separate study, differences between the crude IC value and IC values adjusted for (combinations of) patient sex, age group, reporting quarter and country of origin, with respect to their concordance with a literature comparison were analysed. Comparison was made to the impact on signal detection performance of a triage criterion requiring reports from at least two countries before a drug-ADR pair was highlighted for clinical review. RESULTS: The simulation study demonstrated a clear tendency of the adjusted observed-to-expected ratio to spurious (and considerable) underestimation relative to the crude one, in the presence of any very small strata in a stratified database. With carefully implemented stratification that did not yield any very small strata, this tendency could be avoided. Routine adjustment for potential confounders improved signal detection performance relative to the literature comparison, but the magnitude of the improvement was modest. The improvement from the triage criterion was more considerable. DISCUSSION AND CONCLUSIONS: Our results indicate that first-pass screening based on observed-to-expected ratios adjusted with stratification may lead to missed signals in ADR surveillance, unless very small strata are avoided. In addition, the improvement in signal detection performance due to routine adjustment for a set of common confounders appears to be smaller than previously assumed. Other approaches to improving signal detection performance such as the development of refined triage criteria may be more promising areas for future research.

Statins, neuromuscular degenerative disease and an amyotrophic lateral sclerosis-like syndrome: an analysis of individual case safety reports from vigibase.

BACKGROUND: The WHO Foundation Collaborating Centre for International Drug Monitoring (Uppsala Monitoring Centre [UMC]) has received many individual case safety reports (ICSRs) associating HMG-CoA reductase inhibitor drug (statin) use with the occurrence of muscle damage, including rhabdomyolysis, and also peripheral neuropathy. A new signal has now appeared of disproportionally high reporting of upper motor neurone lesions. AIM AND SCOPE: The aim of this paper is to present the upper motor neurone lesion cases, with other evidence, as a signal of a relationship between statins and an amyotrophic lateral sclerosis (ALS)-like syndrome. The paper also presents some arguments for considering that a spectrum of severe neuromuscular damage may be associated with statin use, albeit rarely. The paper does not do more than raise the signal for further work and analysis of what must be regarded as a potentially very serious and perhaps avoidable or reversible adverse reaction, though it also suggests action to be taken if an ALS-like syndrome should occur in a patient using statins. METHODS: The 43 reports accounting for the disproportional reports in Vigibase (the database of the WHO Programme for International Drug Monitoring) are summarised and analysed for the diagnosis of an ALS-like syndrome. The issues of data quality and potential reporting bias are considered. RESULTS: 'Upper motor neurone lesion' is a rare adverse event reported in relationship to drugs in Vigibase (a database containing nearly 4 million ICSRs). Of the total of 172 ICSRs on this reported term, 43 were related to statins, of which 40 were considered further: all but one case was reported as ALS. In 34/40 reports a statin was the sole reported suspected drug. The diagnostic criteria were variable, and seven of the statin cases also had features of peripheral neuropathy. Of a total of 5534 ICSRs of peripheral neuropathy related to any drug in Vigibase, 547 were on statins. The disproportional reporting of statins and upper motor neurone lesion persisted after age stratification, and such disproportionality was not seen for statins and Parkinson's disease, Alzheimer's disease, extrapyramidal disorders, or multiple sclerosis-like syndromes. DISCUSSION: Because the cases were sometimes atypical we propose the use of the term 'ALS-like syndrome' and speculate whether this is part of a spectrum of rare neuromuscular damage. The diagnosis of ALS is often problematic, and the insidiousness and chronicity of the disease make causality with a drug difficult to assess. The disproportionally high reporting makes this an important signal nevertheless, since ALS is serious clinically and statins are so widely used. Wide use of the statins also makes a chance finding more probable, but is unlikely to cause disproportional reporting when there are no obvious biases identified. CONCLUSION: We emphasise the rarity of this possible association, and also the need for further study to establish whether a causal relationship exists. We do advocate that trial discontinuation of a statin should be considered in patients with serious neuromuscular disease such as the ALS-like syndrome, given the poor prognosis and a possibility that progression of the disease may be halted or even reversed.

Current Safety Concerns with Human Papillomavirus Vaccine: A Cluster Analysis of Reports in VigiBase®.

INTRODUCTION: A number of safety signals-complex regional pain syndrome (CRPS), postural orthostatic tachycardia syndrome (POTS), and chronic fatigue syndrome (CFS)-have emerged with human papillomavirus (HPV) vaccines, which share a similar pattern of symptomatology. Previous signal evaluations and epidemiological studies have largely relied on traditional methodologies and signals have been considered individually. OBJECTIVE: The aim of this study was to explore global reporting patterns for HPV vaccine for subgroups of reports with similar adverse event (AE) profiles. METHODS: All individual case safety reports (reports) for HPV vaccines in VigiBase® until 1 January 2015 were identified. A statistical cluster analysis algorithm was used to identify natural groupings based on AE profiles in a data-driven exploratory analysis. Clinical assessment of the clusters was performed to identify clusters relevant to current safety concerns. RESULTS: Overall, 54 clusters containing at least five reports were identified. The four largest clusters included 71 % of the analysed HPV reports and described AEs included in the product label. Four smaller clusters were identified to include case reports relevant to ongoing safety concerns (total of 694 cases). In all four of these clusters, the most commonly reported AE terms were headache and dizziness and fatigue or syncope; three of these four AE terms were reported in >50 % of the reports included in the clusters. These clusters had a higher proportion of serious cases compared with HPV reports overall (44-89 % in the clusters compared with 24 %). Furthermore, only a minority of reports included in these clusters included AE terms of diagnoses to explain these symptoms. Using proportional reporting ratios, the combination of headache and dizziness with either fatigue or syncope was found to be more commonly reported in HPV vaccine reports compared with non-HPV vaccine reports for females aged 9-25 years. This disproportionality remained when results were stratified by age and when those countries reporting the signals of CRPS (Japan) and POTS (Denmark) were excluded. CONCLUSIONS: Cluster analysis reveals additional reports of AEs following HPV vaccination that are serious in nature and describe symptoms that overlap those reported in cases from the recent safety signals (POTS, CRPS, and CFS), but which do not report explicit diagnoses. While the causal association between HPV vaccination and these AEs remains uncertain, more extensive analyses of spontaneous reports can better identify the relevant case series for thorough signal evaluation.

Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts.

INTRODUCTION: The rapid expansion of the Internet and computing power in recent years has opened up the possibility of using social media for pharmacovigilance. While this general concept has been proposed by many, central questions remain as to whether social media can provide earlier warnings for rare and serious events than traditional signal detection from spontaneous report data. OBJECTIVE: Our objective was to examine whether specific product-adverse event pairs were reported via social media before being reported to the US FDA Adverse Event Reporting System (FAERS). METHODS: A retrospective analysis of public Facebook and Twitter data was conducted for 10 recent FDA postmarketing safety signals at the drug-event pair level with six negative controls. Social media data corresponding to two years prior to signal detection of each product-event pair were compiled. Automated classifiers were used to identify each 'post with resemblance to an adverse event' (Proto-AE), among English language posts. A custom dictionary was used to translate Internet vernacular into Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms. Drug safety physicians conducted a manual review to determine causality using World Health Organization-Uppsala Monitoring Centre (WHO-UMC) assessment criteria. Cases were also compared with those reported in FAERS. FINDINGS: A total of 935,246 posts were harvested from Facebook and Twitter, from March 2009 through October 2014. The automated classifier identified 98,252 Proto-AEs. Of these, 13 posts were selected for causality assessment of product-event pairs. Clinical assessment revealed that posts had sufficient information to warrant further investigation for two possible product-event associations: dronedarone-vasculitis and Banana Boat Sunscreen--skin burns. No product-event associations were found among the negative controls. In one of the positive cases, the first report occurred in social media prior to signal detection from FAERS, whereas the other case occurred first in FAERS. CONCLUSIONS: An efficient semi-automated approach to social media monitoring may provide earlier insights into certain adverse events. More work is needed to elaborate additional uses for social media data in pharmacovigilance and to determine how they can be applied by regulatory agencies.

Pharmacovigilance is... Vigilance.

The world changes continuously and pharmacovigilance as a new discipline also must change. There are new fields opening with novel challenges whilst we are still perfecting ways to manage and improve the basic challenges such as inadequate data for decision making and under-reporting. Traditional medicines, vaccines, poisoning and medication error are all aspects of the safety of medicines that we have monitored for decades, though without perhaps paying enough attention to their special aspects. There are many new stakeholders taking serious interest in pharmacovigilance outside the regulatory sphere and they often focus on improving individual patient care, rather than the more traditional concentration on broad public health. The same stakeholders are also drawing attention to other iatrogenic outcomes that should be recognised, evaluated and their outcomes compared and contrasted with medication, such as harm from medical devices. The vigilance methods used for medication are very much applicable to all these new fields, though more and different expertise will be needed to evaluate outcomes.

Patient-Reported Safety Information: A Renaissance of Pharmacovigilance?

The role of patients as key contributors in pharmacovigilance was acknowledged in the new EU pharmacovigilance legislation. This contains several efforts to increase the involvement of the general public, including making patient adverse drug reaction (ADR) reporting systems mandatory. Three years have passed since the legislation was introduced and the key question is: does pharmacovigilance yet make optimal use of patient-reported safety information? Independent research has shown beyond doubt that patients make an important contribution to pharmacovigilance signal detection. Patient reports provide first-hand information about the suspected ADR and the circumstances under which it occurred, including medication errors, quality failures, and 'near misses'. Patient-reported safety information leads to a better understanding of the patient's experiences of the ADR. Patients are better at explaining the nature, personal significance and consequences of ADRs than healthcare professionals' reports on similar associations and they give more detailed information regarding quality of life including psychological effects and effects on everyday tasks. Current methods used in pharmacovigilance need to optimise use of the information reported from patients. To make the most of information from patients, the systems we use for collecting, coding and recording patient-reported information and the methodologies applied for signal detection and assessment need to be further developed, such as a patient-specific form, development of a severity grading and evolution of the database structure and the signal detection methods applied. It is time for a renaissance of pharmacovigilance.

The WHO World Alliance for Patient Safety: a new challenge or an old one neglected?

The WHO World Alliance on Patient Safety is a new, all encompassing project to improve medical care. Individual patients are the focus and all countries are encouraged to develop systems in which medical error, therapeutic accidents and failures are minimised. The potential for adverse events is present at all levels of healthcare and in all disciplines. One working group in the Alliance is charged with promoting and developing a 'reporting and learning' culture for adverse events in all areas of medical care. Central to current thinking for this group is a no-fault approach and to report near misses. The aim is not to provide certainty over the individual events, but rather to draw attention to possible improvements in systems that may prevent future problems. Adverse events relating to drug therapy have been reported for decades to national pharmacovigilance authorities, but this is aimed at finding problems with the drugs themselves as early as possible. The Alliance approach in the area of drug safety, by contrast, has a greater focus on safety in the systems of drug provision (including prescription and dispensing) and other systematic issues relating to safe drug provision, such as fraudulent drugs. Thus, current pharmacovigilance can be seen as representing a part of the reporting and learning envisaged by the Alliance. The two approaches are also complementary, but there are practical and philosophical areas of overlap in which difficulties may occur, such as anonymised reporting in a no-fault system and consequent impossibility for follow-up. In pharmacovigilance follow-up for more information is regarded as essential. Whether pharmacovigilance broadens into the area of patient safety or the latter involves completely new systems to do its work will be a matter for each country to consider. One thing is certain, working together both systems will improve patient care, but without cooperation more bureaucracy will take valuable health professional time with a lesser result.

A bayesian recurrent neural network for unsupervised pattern recognition in large incomplete data sets.

A recurrent neural network, modified to handle highly incomplete training data is described. Unsupervised pattern recognition is demonstrated in the WHO database of adverse drug reactions. Comparison is made to a well established method, AutoClass, and the performances of both methods is investigated on simulated data. The neural network method performs comparably to AutoClass in simulated data, and better than AutoClass in real world data. With its better scaling properties, the neural network is a promising tool for unsupervised pattern recognition in huge databases of incomplete observations.