14 research outputs found

    What Factors Make EU Regulators Want to Communicate Drug Safety Issues Related to SGLT2 Inhibitors?:An Online Survey Study

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    INTRODUCTION: Previous studies have found differences in the communication of safety issues among medicines regulatory agencies.OBJECTIVES: To explore (1) to what extent regulators' opinions regarding the need to communicate safety issues related to sodium-glucose cotransporter-2 (SGLT2) inhibitors might be influenced by their concern about the safety issue, and (2) whether regulators' concerns might be influenced by certain characteristics of the safety issue or by the demographic and professional characteristics and attitudes of the regulators.METHODS: An online cross-sectional survey study with a rating-based conjoint analysis among clinical and pharmacovigilance assessors from the EU regulatory network was performed between April and June 2021. Regulators were invited by email, and participants were asked about their level of concern and their opinion regarding the need to communicate about 12 scenarios defined by four characteristics: adverse drug reaction, source of information, causality, and frequency. The outcomes for the first objective were to update the summary of product characteristics (SmPC; yes/no) and to send direct healthcare professional communications (DHPC; yes/no). The determinant was regulators' level of concern (range 0-100%). The outcome of the second objective was regulators' level of concern, and the determinants were the characteristics of the safety issue, demographic and professional characteristics, and attitudes of the regulators (beliefs about medicines and risk perception).RESULTS: A total of 222 regulators completed the survey (64% women; mean age 46 ± 10 years). Depending on the scenario, 54-94% and 25-74% of the participants would update the SmPC or send a DHPC, respectively. The participants' level of concern influenced their opinions regarding the need to update the SmPC and send a DHPC (odds ratio (OR) 13.0; 95% confidence interval (CI) 7.8-21.7 and OR 13.6; 95% CI 9.5-19.2, respectively, for every 10% increase in the level of concern). All characteristics of the safety issue influenced the level of concern. Younger participants, women, and those working for Eastern European agencies had a higher level of concern than older participants, men, and those working in other regions. Beliefs about medicines and general risk perception also influenced their concern.CONCLUSIONS: The opinion regarding the need to communicate safety issues was influenced by the concern of regulators. Regulators' concern was influenced by the characteristics of the safety issue, demographic characteristics, and attitudes. Diverse groups of experts regarding such factors would ensure that various views are incorporated in risk communication decisions.</p

    Characteristics of drugs safety signals that predict safety related product information update

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    Purpose: Investigation of drug safety signals is one of the major tasks in pharmacovigilance. Among many potential signals identified, only a few reflect adverse drug reactions requiring regulatory actions, such as product information (PI) update. Limited information is available regarding the signal characteristics that might predict PI update following signal evaluation. The objective of this study was to identify signal characteristics associated with PI updates following signal evaluation by the European Medicines Agency Pharmacovigilance Risk Assessment Committee during 2012 to 2016. Methods: A comparative study was performed based on data from 172 safety signals. Characteristics of signals were extracted from the European Pharmacovigilance Issues Tracking Tool database. Multivariable logistic regression analysis was used to assess the relationship between signal characteristics and the decision to update the PI. Results: Multivariable logistic regression analysis showed that the presence of evidence in multiple types of data sources (adjusted odds ratio [OR] 7.8 95% CI [1.5, 40.1]); mechanistic plausibility of the drug-event association (adjusted OR 3.9 95% CI [1.9, 8.0]); seriousness of the event (adjusted OR 4.2 95% CI [1.3, 13.9]); and age of drugs ≤5 years (adjusted OR 3.9 95% CI [1.2, 12.7]) were associated with the decision to change the PI (P < 0.05). Conclusions: This study identified 4 characteristics of drug safety signals that have shown to be associated with PI changes as outcome of signal evaluation. These characteristics may be used as criteria for selection and prioritization of potential signals that are more likely to necessitate product information updates

    Methods to identify the target population: implications for prescribing quality indicators

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    Background: Information on prescribing quality is increasingly used by policy makers, insurance companies and health care providers. For reliable assessment of prescribing quality it is important to correctly identify the patients eligible for recommended treatment. Often either diagnostic codes or clinical measurements are used to identify such patients. We compared these two approaches regarding the outcome of the prescribing quality assessment and their ability to identify treated and undertreated patients. Methods: The approaches were compared using electronic health records for 3214 diabetes patients from 70 general practitioners. We selected three existing prescribing quality indicators (PQI) assessing different aspects of treatment in patients with hypertension or who were overweight. We compared population level prescribing quality scores and proportions of identified patients using definitions of hypertension or being overweight based on diagnostic codes, clinical measurements or both. Results: The prescribing quality score for prescribing any antihypertensive treatment was 93% (95% confidence interval 90-95%) using the diagnostic code-based approach, and 81% (78-83%) using the measurement-based approach. Patients receiving antihypertensive treatment had a better registration of their diagnosis compared to hypertensive patients in whom such treatment was not initiated. Scores on the other two PQI were similar for the different approaches, ranging from 64 to 66%. For all PQI, the clinical measurement -based approach identified higher proportions of both well treated and undertreated patients compared to the diagnostic code -based approach. Conclusions: The use of clinical measurements is recommended when PQI are used to identify undertreated patients. Using diagnostic codes or clinical measurement values has little impact on the outcomes of proportion-based PQI when both numerator and denominator are equally affected. In situations when a diagnosis is better registered for treated than untreated patients, as we observed for hypertension, the diagnostic code-based approach results in overestimation of provided treatment

    The community impact of the 2009 influenza pandemic in the WHO European Region: a comparison with historical seasonal data from 28 countries

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    Contains fulltext : 109779.pdf (publisher's version ) (Open Access)BACKGROUND: The world has recently experienced the first influenza pandemic of the 21st century that lasted 14 months from June 2009 to August 2010. This study aimed to compare the timing, geographic spread and community impact during the winter wave of influenza pandemic A (H1N1) 2009 to historical influenza seasons in countries of the WHO European region. METHODS: We assessed the timing of pandemic by comparing the median peak of influenza activity in countries of the region during the last seven influenza seasons. The peaks of influenza activity were selected by two independent researchers using predefined rules. The geographic spread was assessed by correlating the peak week of influenza activity in included countries against the longitude and latitude of the central point in each country. To assess the community impact of pandemic influenza, we constructed linear regression models to compare the total and age-specific influenza-like-illness (ILI) or acute respiratory infection (ARI) rates reported by the countries in the pandemic season to those observed in the previous six influenza seasons. RESULTS: We found that the influenza activity reached its peak during the pandemic, on average, 10.5 weeks (95% CI 6.4-14.2) earlier than during the previous 6 seasons in the Region, and there was a west to east spread of pandemic A(H1N1) influenza virus in the western part of the Region. A regression analysis showed that the total ILI or ARI rates were not higher than historical rates in 19 of the 28 countries. However, in countries with age-specific data, there were significantly higher consultation rates in the 0-4 and/or 5-14 age groups in 11 of the 20 countries. CONCLUSIONS: Using routine influenza surveillance data, we found that pandemic influenza had several differential features compared to historical seasons in the region. It arrived earlier, caused significantly higher number of outpatient consultations in children in most countries and followed west to east spread that was previously observed during some influenza seasons with dominant A (H3N2) ifluenza viruses. The results of this study help to understand the epidemiology of 2009 influenza pandemic and can be used for pandemic preparedness planning

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

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    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

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

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    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

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

    No full text
    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
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