Adverse reactions following MPox (monkeypox) vaccination: An overview from the Dutch and global adverse event reporting systems.

AIMS: The spreading of MPox (monkeypox) virus led to a vaccination campaign in the Netherlands for individuals at high risk of infection. This overview elucidates the characteristics of the reported adverse events following immunization (AEFI) following active immunization against monkeypox and thereby provides insight on the safety profile in daily practice. METHODS: Data were collected from the spontaneous reporting system of the Netherlands Pharmacovigilance Centre Lareb. Furthermore, the global database of the World Health Organization was consulted on globally reported AEFI following smallpox or monkeypox immunization in 2022. RESULTS: Until 15 November 2022, 148 unique individual case safety reports (ICSRs) regarding monkeypox vaccination were received at Lareb. Two ICSRs reported a serious outcome (1.4%). A total of 2205 ICSRs were received in the global database in 2022, of which 131 reports (5.9%) concerned a serious reaction. Reported AEFI in both databases mainly included injection site reactions and general systemic reactions commonly observed after vaccination. CONCLUSION: The pattern of reported AEFI for monkeypox vaccines both in the Dutch and global ICSR database is generally in accordance with the manufacturer's product information and consists largely of injection site reactions and nonserious AEFI related to systemic reactogenicity.

A case series of bacillus Calmette-Guérin scar reactivation after administration of both mRNA and viral vector COVID-19 vaccines.

AIM: Reactivation of the scar resulting from intradermal injection of bacillus Calmette-Guérin (BCG) is a common specific reaction in Kawasaki's disease. It has also sporadically been associated with viral infections, multisystem inflammatory syndrome in children, influenza vaccination and mRNA COVID-19 vaccination. In this case series, characteristics of BCG scar reactivation after different COVID-19 vaccinations are presented and possible mechanisms are discussed. METHODS: Data were collected from the spontaneous reporting system of the Netherlands Pharmacovigilance Centre Lareb. Descriptives were made for the case reports in which a BCG scar reactivation was detected. RESULTS: Since the start of the COVID-19 vaccination campaign in January 2021, the Netherlands Pharmacovigilance Centre Lareb has received 22 case reports of BCG reactivation after vaccination with a COVID-19 vaccine. In 20 case reports, it concerned mRNA COVID-19 vaccines Moderna (14) and Pfizer (6). In two case reports, the viral vector COVID-19 vaccine AstraZeneca was administered. Erythema and pain were the most frequently reported symptoms and the size of the inflammation was between 1.5 and 5 cm. BCG scar reactivation occurred with a median time to onset of 2 days after the second or booster COVID-19 vaccination, whereas the median time to onset was 7 days after the first COVID-19 vaccination. None of the BCG scar reactivations were treated. CONCLUSIONS: The exact mechanism of the occurrence of BCG scar reactivation remains unknown, but involvement of heat shock protein 65 is suggested. BCG scar reactivation is a nonserious, self-limiting reaction that can occur after vaccination with both mRNA and viral vector COVID-19 vaccines.

Menstrual abnormalities after COVID-19 vaccination in the Netherlands: A description of spontaneous and longitudinal patient-reported data.

AIMS: During the COVID-19 vaccination campaigns, the number of reports of menstrual abnormalities increased rapidly. Here, we describe the nature and potential risk factors associated with menstrual abnormalities based on spontaneously reporting data as well as data from a prospective cohort event monitoring (CEM) study as these are poorly studied. METHODS: Reports of menstrual abnormalities received by the Netherlands Pharmacovigilance Centre Lareb in the spontaneous reporting system between February 2021 and April 2022 were summarized. In addition, logistic regression analysis was performed on the reported menstrual abnormalities in the CEM study to assess the association between person characteristics, prior SARS-CoV-2 infection and use of hormonal contraceptives and the occurrence of menstrual abnormalities after vaccination. RESULTS: We analysed over 24 000 spontaneous reports of menstrual abnormalities and over 500 episodes (among 16 929 included women) of menstrual abnormalities in the CEM study. The CEM study showed an incidence of 41.4 per 1000 women aged ≤54 years. Amenorrhoea/oligomenorrhoea and heavy menstrual bleeding collectively accounted for about half of all abnormalities reported. Significant associations were observed for the age group 25-34 years (odds ratio 2.18; 95% confidence interval 1.45-3.41) and the Pfizer vaccine (odds ratio 3.04; 95% confidence interval 2.36-3.93). No association was observed for body mass index and presence of most comorbidities assessed. CONCLUSION: The cohort study showed a high incidence of menstrual disorders among women aged ≤54 years, and this observation was supported by the analysis of spontaneous reports. This suggests that a relation between COVID-19 vaccination and menstrual abnormalities is plausible and should be further investigated.

Observed-over-Expected analysis as additional method for pharmacovigilance signal detection in large-scaled spontaneous adverse event reporting.

BACKGROUND: The large-scale COVID-19 vaccination campaigns in 2021 and 2022 led to a rapid increase in numbers of received adverse event reports in spontaneous reporting systems. As background incidences of naturally occurring medical events became increasingly relevant for causality assessment of potential associations with the vaccines, a novel approach for signal detection was warranted. OBJECTIVES: This article illustrates the Observed-over-Expected (O/E) analysis as an additional method for signal detection and risk assessment in large-scaled spontaneous reporting systems. METHODS: All individual case safety reports (ICSRs) concerning idiopathic peripheral facial paralysis or Bell's palsy following administration of the COVID-19 vaccines (n = 291) manufactured by Pfizer/BioNTech (Comirnaty), Moderna (Spikevax), AstraZeneca (Vaxzevria) and Janssen (JCOVDEN) received by the National Pharmacovigilance Centre Lareb until 24th March 2022 were included in the O/E analysis, within a risk window of 7 and 14 days following immunisation. Dutch background incidence rates from 2019 and exposure of the Dutch population to the vaccines were obtained from the PHARMO institute and RIVM. The data was stratified in age groups, gender and administered dose in order to differentiate between population subgroups. RESULTS: Bell's palsy was reported more frequently than expected in several population subgroups following administration of all four COVID-19 vaccines, including children and adolescents. Among children, a high O/E ratio was found for boys aged 5-14 years after receiving the Pfizer/BioNTech vaccine. Regarding adolescents and young adults, women aged 15-24 years receiving Pfizer/BioNTech and Moderna, and men aged 15-24 years receiving Janssen developed Bell's palsy more often than expected. Furthermore, O/E ratios were high for individuals aged 25-64, regarding females receiving Pfizer, Moderna and AstraZeneca and males receiving Janssen. As facial paralysis was not labelled as an adverse event for the Janssen vaccine, this analysis contributed to signalling the association and warranting further regulatory action. CONCLUSIONS: The O/E method is a useful approach for signal detection of potential adverse reactions when handling large numbers of ICSRs. Further research is needed to attest to the causality on a clinical basis.

Safety assessment and adverse drug reaction reporting of tea tree oil (Melaleuca aetheroleum).

Tea tree (Melaleuca alternifolia) essential oil is widely used as an antiseptic. It mainly consists of monoterpenes with terpinen-4-ol as the major constituent. The aim of this study was to review literature on safety data about tea tree oil and to assess its safety by investigating 159 cases of adverse reactions possibly caused by the oil, reported to the World Health Organization (WHO) from December 1987 until September 2021. To extract these data, VigiBase, the WHO global database of individual case safety reports maintained by the Uppsala Monitoring Centre (UMC), was used. All cases were categorized and analysed and 16 serious cases further assessed. It was concluded that tea tree oil should never be administered orally, as it can lead to central nervous system depression and pneumonitis. Applied topically, skin disorders may occur, especially when the oil had been exposed to light or air. This yields monoterpene oxidation products, being potent skin irritants. Tea tree oil stored under appropriate conditions and not exceeding the expiration date should be considered safe to use by non-vulnerable people for non-serious inflammatory skin conditions, although the occurrence of adverse reactions such as contact allergies is difficult to predict.

Numbers of spontaneous reports: How to use and interpret?

Due to the high intensity of the COVID-19 vaccination campaigns and heightened attention for safety issues, the number of spontaneous reports has surged. In the Netherlands, pharmacovigilance centre Lareb has received more than 100 000 reports on adverse events following immunization (AEFI) associated with Covid-19 vaccination. It is tempting to interpret absolute numbers of reports of AEFIs in signal detection. Signal detection of spontaneously reported adverse drug reactions has its origin in case-by-case analysis, where all case reports are assessed by clinically qualified assessors. The concept of clinical review of cases-even if only a few per country-followed by sharing concerns of suspicions of potential adverse reactions again proved the strength of the system. Disproportionality analysis can be useful in signal identification, and comparing reported cases with expected based on background incidence can be useful to support signal detection. However, they cannot be used without an in-depth analysis of the underlying clinical data and pharmacological mechanism. This in-depth analysis has been performed, and is ongoing, for the signal of vaccine-induced immune thrombotic thrombocytopenia (VITT) in relation to the AstraZeneca and Janssen Covid-19 vaccines. Although not frequency or incidence rates, reporting rates can provide an impression of the occurrence of the event. But the unknown underreporting should also be part of this context. To quantify the incidence rates, follow-up epidemiological studies are needed.

Using structural topic modelling to reveal patterns in reports on opioid drugs in a pharmacovigilance database.

BACKGROUND: Adverse drug reaction (ADR) reports in pharmacovigilance databases often contain coded information and large amounts of unstructured or semi-structured information in plain text format. The unstructured format and sheer volume of these data often render them neglected. Structural topic modelling (STM) represents a potentially insightful way of harnessing these valuable data and to detect grouping or themes in spontaneous reports to aid signal detection. PURPOSE: This was an explorative study of the potential for structural topic modelling to identify useful patterns in ADR reports involving opioid drugs in a pharmacovigilance database. METHODS: A dataset of ADR reports on opioid drugs reported to the Netherlands Pharmacovigilance Centre Lareb from 1991 to December 2020 was used, comprising a total of 3069 unique reports. Qualitative text analysis was combined with STM, an automated text analysis method, to examine these data. RESULTS: In reports submitted directly by patients and healthcare professionals, 11 meaningful topics were identified, whereby patient experience reports, particularly in relation to pain (relief), and the timing of intake and ADRs of tramadol and paracetamol, were the most common. Of the 12 topics identified in reports received via marketing authorization holders, patch and skin-related side effects, addiction and constipation were the most prevalent. CONCLUSIONS: The STM-based analysis identified information that cannot always be captured by coding with the Medical Dictionary for Regulatory Activities (MedDRA®). The identified topics reflect findings in the literature on opioids.

Development of a multivariate prediction model to identify individual case safety reports which require clinical review.

BACKGROUND: The number of Individual Case Safety Reports (ICSRs) in pharmacovigilance databases are rapidly increasing world-wide. The majority of ICSRs at the Netherlands Pharmacovigilance Centre Lareb is reviewed manually to identify potential signal triggering reports (PSTR) or ICSRs which need further clinical assessment for other reasons. OBJECTIVES: To develop a prediction model to identify ICSRs that require clinical review, including PSTRs. Secondly, to identify the most important features of these reports. METHODS: All ICSRs (n = 30 424) received by Lareb between October 1, 2017 and February 26, 2021 were included. ICSRs originating from marketing authorisation holders and ICSRs reported on vaccines were excluded. The outcome was defined as PSTR (yes/no), where PSTR 'yes' was defined as an ICSR discussed at a signal detection meeting. Nineteen features were included, concerning structured information on: patients, adverse drug reactions (ADR) or drugs. Data were divided into a training (70%) and test set (30%) using a stratified split to maintain the PSTR/no PSTR ratio. Logistic regression, elastic net logistic regression and eXtreme Gradient Boosting models were trained and tuned on a training set. Random down-sampling of negative controls was applied on the training set to adjust for the imbalanced dataset. Final models were evaluated on the test set. Model performances were assessed using the area under the curve (AUC) with 95% confidence interval of a receiver operating characteristic (ROC), and specificity and precision were assessed at a threshold for perfect sensitivity (100%, to not miss any PSTRs). Feature importance plots were inspected and a selection of features was used to re-train and test model performances with fewer features. RESULTS: 1439 (4.7%) of reports were PSTR. All three models performed equally with a highest AUC of 0.75 (0.73-0.77). Despite moderate model performances, specificity (5%) and precision (5%) were low. Most important features were: 'absence of ADR in the Summary of product characteristics', 'ADR reported as serious', 'ADR labelled as an important medical event', 'ADR reported by physician' and 'positive rechallenge'. Model performances were similar when using only nine of the most important features. CONCLUSIONS: We developed a prediction model with moderate performances to identify PSTRs with nine commonly available features. Optimisation of the model using more ICSR information (e.g., free text fields) to increase model precision is required before implementation.

Global Risk of Bacterial Skin Infections and Herpesviridae Infections with Ustekinumab, Secukinumab, and Tumour Necrosis Factor-alpha Inhibitors: Spontaneous Reports of Adverse Drug Reactions from the World Health Organization Pharmacovigilance Center.

Genetic defects in interleukin-12/23/17 immunity are associated with an increased risk of Staphylococcus aureus and herpesvirus skin infections. This study analysed spontaneous safety reports from the WHO Pharmacovigilance Center of bacterial skin or herpesvirus infections associated with secukinumab, ustekinumab and tumour necrosis factor-α inhibitors. Associations found in disproportionality analyses were expressed as reporting odds ratios (ROR). For bacterial skin infections, ustekinumab showed the strongest association (ROR 6.09; 95% confidence interval (95% CI) 5.44-6.81), and, among the tumour necrosis factor-α inhibitors, infliximab showed the strongest association (ROR 4.18; 95% CI 3.97-4.40). Risk was comparable between infliximab and secukinumab (ROR 3.51; 95% CI 3.00-4.09). Secukinumab showed the strongest association with herpes simplex infection (ROR 4.80; 95% CI 3.78-6.10). All biologics were equally associated with herpes zoster. Infliximab was the only biologic associated with cytomegalovirus infection (ROR 5.66; 95% CI 5.08-6.31) and had the strongest association with Epstein-Barr virus infection (ROR 6.90; 95% CI 6.03-7.90). All biologics evaluated were positively associated with bacterial skin infections, herpes simplex, and herpes zoster, compared with all other drugs in the WHO database for which individual case safety reports were collected. The possibility of under-reporting, reporting bias and difference in causality assessment between countries and reporters must be taken into account when interpreting the results of disproportionality analyses.

Red yeast rice (Monascus purpureus) supplements: Case series assessment of spontaneously reported cases to The Netherlands Pharmacovigilance Centre Lareb.

Serious concerns are expressed on the safe use of red yeast rice (RYR) supplements. The aim of the present study was to analyse cases received by Lareb on RYR-related adverse health events. These cases were analysed for the number of reports, number of adverse drug reactions (ADRs), causality, seriousness of the reaction, latency-period, age and sex of the patients, concomitant medication and type of reporter. A total of 94 individual reports were collected by Lareb, corresponding with 187 ADRs. The analysis showed most reported ADRs were labelled musculoskeletal and connective tissue disorders (n = 64), gastrointestinal disorders (n = 33) and general disorders and administration site conditions (n = 23). The use of RYR supplements should be considered as a significant safety concern. Exposure to monacolin K could lead to serious adverse effects. To fully assess the safety profile of RYR supplements, more research is necessary to compose a complete ADR profile of RYR supplements.

Unexpected beneficial effects of drugs: an analysis of cases in the Dutch spontaneous reporting system.

INTRODUCTION: Drug use is inherently related to both beneficial effects on health as well as the occurrence of risks. The beneficial effects may be related to efficacy, the treatment range of a product, or even to user-friendliness of a product. However, in addition to the occurrence of adverse drug reactions, a drug can also have an unexpected beneficial effect on a patient's health, not related to the indication for which the drug was used. The aim of this article is to characterize the reports of unexpected beneficial effects of drugs in the Dutch spontaneous reporting system. METHODS: A descriptive analysis was used to gain insight in number of reports and drug classes responsible for unexpected beneficial effects of drugs. Grouping of positive side effects into classes was done by a conventional qualitative content analysis of the cases. RESULTS: Four hundred nine reports which described unexpected beneficial effects of drugs were included, which mentioned 451 associations between suspected drugs and unexpected beneficial effects. There were 147 drug classes on the 4th ATC level involved. Content analysis of the reports gave rise to 22 categories of unexpected beneficial effects of drugs, including one "other category". DISCUSSION AND CONCLUSION: The analysis showed a diverse spectrum of reported reactions and drugs with some categories of unexpected beneficial effects of drugs mentioned multiple times for certain drug classes on the 4th ATC level. Most of these findings are consistent with the existing literature and knowledge on the pharmacological mechanism of the drugs in question. Coding harmonization would make it possible to study these effects in international databases.

Signals from the Dutch national spontaneous reporting system: Characteristics and regulatory actions.

PURPOSE: The aim of the study is to characterise safety signals based on the Dutch spontaneous reporting system (SRS) and to investigate the association between signal characteristics and Product Information (PI) update stratified by approval type: centrally authorised products (CAPs) versus nationally and decentralised authorised products (NAPs). METHODS: This study evaluates the full cohort of signals disseminated from the Dutch SRS in the period from 2008 to 2017. Each retrieved signal was characterised on a number of aspects. The signal management process from signal generation to a potential PI update was analysed in four steps: (1) signal characterisation; (2) proposed actions by the Dutch national competent authority (NCA) for the signals; (3) presence of PI update (yes/no) and association with signal characteristics; (4) timing from the moment the signal was issued to PI update. For step 1-3 we stratified products in CAPs and NAPs. RESULTS: Of all signals, 88.7% led to a proposed regulatory action by the NCA. Signals from the Dutch SRS for CAPs versus NAPs more often concerned biologicals, important medical events, class effects and shorter periods since marketing authorization. We detected PI updates for 26.2% of CAP signals and 61.3% of NAP signals. CONCLUSIONS: The Dutch SRSs remains an important source of signals. There are some notable differences in the characteristics of signals for CAPs versus NAPs. Signals for NAPs more frequently led to PI updates.

Opportunities for changes in the drug product design to enhance medication safety in older people: Evaluation of a national public portal for medication incidents.

AIMS: Medication safety requires urgent attention in hospital pharmacy. This study evaluated the medication-related problems/errors as reported to the Dutch medication incident registry and disseminated for information to pharmacists. Through analysis by an expert panel we aimed to better understand which problems could have been mitigated by the drug product design. Additionally, the (wider) implications of the problems for current hospital/clinical practice were discussed. METHODS: Items were extracted from the public Portal for Patient Safety. Items were included if relevant for older people and connected with the drug product design and excluded if they should reasonably have been intercepted by compliance to routine controls or well-known professional standards in pharmaceutical care. To explore any underreporting of well-known incidents, it was investigated if different medication-related problems could be observed in a regional hospital practise over a 1-month period. For 6 included items (cases), the implications for hospital/clinical practise were discussed in an expert panel. RESULTS: In total, 307 items were identified in the Portal for Patient Safety; all but 14 were excluded. Six cases were added from daily hospital practice. These 20 cases commonly related to confusing product characteristics, packaging issues such as the lack of a single unit package for an oncolytic product, or incorrect or incomplete user instructions. CONCLUSION: Medication registries provide important opportunities to evaluate real-world medication-related problems. However, underreporting of well-known problems should be considered. The product design can be used as an (additional) risk mitigation measure to support medication safety in hospital practice.

Time to onset in statistical signal detection revisited: A follow-up study in long-term onset adverse drug reactions.

PURPOSE: In a previous study, we developed a signal detection method using the time to onset (TTO) of adverse drug reactions (ADRs). The aim of the current study was to investigate this method in a subset of ADRs with a longer TTO and to compare its performance with disproportionality analysis. METHODS: Using The Netherlands's spontaneous reporting database, TTO distributions for drug-ADR associations with a median TTO of 7 days or more were compared with other drugs with the same ADR using the two-sample Anderson-Darling (AD) test. Presence in the Summary of Product Characteristics (SPC) was used as the gold standard for identification of a true ADR. Twelve combinations with different values for the number of reports and median TTO were tested. Performance in terms of sensitivity and positive predictive value (PPV) was compared with disproportionality analysis. A sensitivity analysis was performed to compare the results with those from the previous study. RESULTS: A total of 38 017 case reports, containing 32 478 unique drug-ADR associations. Sensitivity was lower for the TTO method (range 0.08-0.34) compared with disproportionality analysis (range 0.60-0.87), whereas PPV was similar for both methods (range 0.93-1.0). The results from the sensitivity analysis were similar to the original analysis. CONCLUSIONS: Because of its low sensitivity, the developed TTO method cannot replace disproportionality analysis as a signal detection tool. It may be useful in combination with other methods.

Does patient reporting lead to earlier detection of drug safety signals? A retrospective comparison of time to reporting between patients and healthcare professionals in a global database.

AIMS: To explore if there is a difference between patients and healthcare professionals (HCPs) in time to reporting drug-adverse drug reaction (ADR) associations that led to drug safety signals. METHODS: This was a retrospective comparison of time to reporting selected drug-ADR associations which led to drug safety signals between patients and HCPs. ADR reports were selected from the World Health Organization Global database of individual case safety reports, VigiBase. Reports were selected based on drug-ADR associations of actual drug safety signals. Primary outcome was the difference in time to reporting between patients and HCPs. The date of the first report for each individual signal was used as time zero. The difference in time between the date of the reports and time zero was calculated. Statistical differences in timing were analysed on the corresponding survival curves using a Mann-Whitney U test. RESULTS: In total, 2822 reports were included, of which 52.7% were patient reports, with a median of 25% for all included signals. For all signals, median time to signal detection was 10.4 years. Overall, HCPs reported earlier than patients: median 7.0 vs. 8.3 years (P < 0.001). CONCLUSIONS: Patients contributed a large proportion of reports on drug-ADR pairs that eventually became signals. HCPs reported 1.3 year earlier than patients. These findings strengthen the evidence on the value of patient reporting in signal detection and highlight an opportunity to encourage patients to report suspected ADRs even earlier in the future.

A prediction model-based algorithm for computer-assisted database screening of adverse drug reactions in the Netherlands.

PURPOSE: The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model-based approach. METHODS: A logistic regression-based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug-ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations. RESULTS: A total of 25 026 unique drug-ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734-0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%). CONCLUSIONS: A prediction model-based approach can be a useful tool to create priority-based listings for signal detection in databases consisting of spontaneous ADRs.

The contribution of direct patient reported ADRs to drug safety signals in the Netherlands from 2010 to 2015.

PURPOSE: The purpose of this study was to investigate the contribution of patient reports to signals sent by the Netherlands Pharmacovigilance Centre Lareb to the Dutch Medicines Evaluation Board and to determine if there are certain types of signals where patient report add a distinct contribution. METHOD: All signals from 2010 until 2015 were included. First, we investigated how many patient reports were present in the signals and the characteristics of these reports compared to the health care professional and marketing authorization holders' reports. In addition to source, the analysis included ATC code of the drug, MedDRA® system organ class and preferred term for the adverse drug reaction (ADR), seriousness of the ADR, and 7 other factors like reports on over-the-counter medication, and how often an ADR listed in the important medical event terms list was present. Secondly, we determined the proportion of reports submitted by the individual groups to signals, in a cross-sectional manner. RESULTS: A total of 150 signals were included, including 1691 ADR reports. Our results show that 26.3% of all ADR reports in Dutch drug safety signals were reported by patients, and 30.5% of the patient reports in the signals contained one or more terms listed as important medical events. The proportion of reports by patients which were included the signals was 2% and 3.9% for health care professional reports and 0.2% for marketing authorization holders reports. CONCLUSION: Patients had an important contribution to signals overall, but especially for ADRs related to generic drug substitution and psychiatric ADRs.

Muscle rupture associated with statin use.

AIM: Statins are used in the treatment of hyperlipidaemia. They are among the most commonly prescribed drugs worldwide. Statins have been linked to musculoskeletal adverse drug reactions. However muscle rupture has not been discussed as an adverse drug reaction to statins so far. The aim of this article is to give an overview of cases of muscle rupture associated with the use of statins. METHOD: We analyzed the cases of muscle rupture associated with the use of statins that were collected by the Netherlands Pharmacovigilance Centre Lareb complemented with the review of cases from the EudraVigilance database. RESULTS: Fifteen cases of muscle rupture associated with statin use have been identified in the database of the Netherlands Pharmacovigilance Centre. Overall, there was a plausible temporal association of events in most cases. In addition, the EudraVigilance database contained 165 reports of muscle rupture reported in patients using statins. Muscle rupture was disproportionally associated with statin use in both databases. The reporting odds ratio was 23.4 (95% CI 11.9, 46.0) and 14.6 (95% CI 12.3, 17.2), respectively. CONCLUSION: Data from spontaneous reporting systems suggest that use of statins is associated with muscle rupture. Physicians and patients should be aware that this can occur.

The validity and reliability of a signal impact assessment tool.

BACKGROUND: The Netherlands Pharmacovigilance Centre Lareb uses an operating Signal Impact Assessment Tool (SIAT) as aid in signal selection. SIAT prioritized signals into one of four categories: strong/moderate signal strength and similarly health impact. Although the SIAT has been used for many years, validity and reliability was never explored. PURPOSE: The aim of this study is to test the validity and reliability of the operating and weight-adjusted SIAT. METHOD: For validity testing, judgments of a Delphi panel of three pharmacovigilance experts were used as a 'gold standard'. First, the panel judged the weighting of the items included in the SIAT. Then, during two phases, the panel rated 40 signals in one of the four categories. Two researchers scored the signals using the SIAT. Panel judgments were compared with scores for the operating and weight-adjusted SIAT. Inter- and intra-observer variability was also tested. The Cohen's Kappa coefficient (k) was calculated. At least substantial agreement (k > 0.6) was considered to be necessary for an acceptable reliability. RESULTS: Validity did not meet predefined criteria: operating and weight-adjusted tool, respectively, k-phase1 = 0.83 and 0.83, k-phase2 = 0.18 and 0.36. Differences were found for signal strength and health impact. Inter- and intra-observer variabilities were good, k of 0.78 and 0.72, respectively. CONCLUSIONS: The SIAT was found to have an insufficient validity and proper reliability. Although SIAT scores should not be decisive in the decision making process, items included can be used as an aid to decide which signals deserve further investigation. Copyright © 2016 John Wiley & Sons, Ltd.