Enhanced Safety Surveillance of Influenza Vaccines in General Practice, Winter 2015-16: Feasibility Study

BACKGROUND: The European Medicines Agency (EMA) requires vaccine manufacturers to conduct enhanced real-time surveillance of seasonal influenza vaccination. The EMA has specified a list of adverse events of interest to be monitored. The EMA sets out 3 different ways to conduct such surveillance: (1) active surveillance, (2) enhanced passive surveillance, or (3) electronic health record data mining (EHR-DM). English general practice (GP) is a suitable setting to implement enhanced passive surveillance and EHR-DM. OBJECTIVE: This study aimed to test the feasibility of conducting enhanced passive surveillance in GP using the yellow card scheme (adverse events of interest reporting cards) to determine if it has any advantages over EHR-DM alone. METHODS: A total of 9 GPs in England participated, of which 3 tested the feasibility of enhanced passive surveillance and the other 6 EHR-DM alone. The 3 that tested EPS provided patients with yellow (adverse events) cards for patients to report any adverse events. Data were extracted from all 9 GPs' EHRs between weeks 35 and 49 (08/24/2015 to 12/06/2015), the main period of influenza vaccination. We conducted weekly analysis and end-of-study analyses. RESULTS: Our GPs were largely distributed across England with a registered population of 81,040. In the week 49 report, 15,863/81,040 people (19.57% of the registered practice population) were vaccinated. In the EPS practices, staff managed to hand out the cards to 61.25% (4150/6776) of the vaccinees, and of these cards, 1.98% (82/4150) were returned to the GP offices. Adverse events of interests were reported by 113 /7223 people (1.56%) in the enhanced passive surveillance practices, compared with 322/8640 people (3.73%) in the EHR-DM practices. CONCLUSIONS: Overall, we demonstrated that GPs EHR-DM was an appropriate method of enhanced surveillance. However, the use of yellow cards, in enhanced passive surveillance practices, did not enhance the collection of adverse events of interests as demonstrated in this study. Their return rate was poor, data entry from them was not straightforward, and there were issues with data reconciliation. We concluded that customized cards prespecifying the EMA's adverse events of interests, combined with EHR-DM, were needed to maximize data collection. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2016-015469

ADVANCE system testing: Can safety studies be conducted using electronic healthcare data? An example using pertussis vaccination

Introduction: The Accelerated Development of Vaccine benefit-risk Collaboration in Europe (ADVANCE) public-private collaboration, aimed to develop and test a system for rapid benefit-risk monitoring of vaccines using healthcare databases in Europe. The objective of this proof-of-concept (POC) study was to test the feasibility of the ADVANCE system to generate incidence rates (IRs) per 1000 person-years and incidence rate ratios (IRRs) for risks associated with whole cell- (wP) and acellular- (aP) pertussis vaccines, occurring in event-specific risk windows in children prior to their pre-school-entry booster. Methods: The study population comprised almost 5.1 million children aged 1 month to <6 years vaccinated with wP or aP vaccines during the study period from 1 January 1990 to 31 December 2015. Data from two Danish hospital (H) databases (AUH and SSI) and five primary care (PC) databases from, UK (THIN and RCGP RSC), Spain (SIDIAP and BIFAP) and Italy (Pedianet) were analysed. Database-specific IRRs between risk vs. non-risk periods were estimated in a self-controlled case series study and pooled using random-effects meta-analyses. Results: The overall IRs were: fever, 58.2 (95% CI: 58.1; 58.3), 96.9 (96.7; 97.1) for PC DBs and 8.56 (8.5; 8.6) for H DBs; convulsions, 7.6 (95% CI: 7.6; 7.7), 3.55 (3.5; 3.6) for PC and 12.87 (12.8; 13) for H; persistent crying, 3.9 (95% CI: 3.8; 3.9) for PC, injection-site reactions, 2.2 (95% CI 2.1; 2.2) for PC, hypotonic hypo-responsive episode (HHE), 0.4 (95% CI: 0.4; 0.4), 0.6 (0.6; 0.6) for PC and 0.2 (0.2; 0.3) for H; and somnolence: 0.3 (95% CI: 0.3; 0.3) for PC. The pooled IRRs for persistent crying, fever, and ISR, adjusted for age and healthy vaccinee period were higher after wP vs. aP vaccination, and lower for convulsions, for all doses. The IRR for HHE was slightly lower for wP than aP, while wP was associated with somnolence only for dose 1 and dose 3 compared with aP. Conclusions: The estimated IRs and IRRs were comparable with published data, therefore demonstrating that the ADVANCE system was able to combine several European healthcare databases to assess vaccine safety data for wP and aP vaccination

ADVANCE system testing: Estimating the incidence of adverse events following pertussis vaccination in healthcare databases with incomplete exposure data

The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public–private collaboration aiming to develop and test a system for rapid vaccine benefit-risk monitoring using existing European healthcare databases. Incidence rate (IR) estimates of vaccination-associated adverse events that are needed to model vaccination risks can be calculated from existing healthcare databases when vaccination (exposure) data are available. We assessed different methods to derive IRs in risk periods following vaccination when exposure data are missing in one database, using estimated IRs and IRRs from other databases for febrile seizures, fever and persistent crying. IRs were estimated for children aged 0–5 years in outcome-specific risk and non-risk periods following the first dose of acellular pertussis (aP) vaccination in four primary care databases and one hospital database. We compared derived and observed IRs in each database using three methods: 1) multiplication of non-risk period IR for database i by IR ratio (IRR) obtained from meta-analysis of IRRs estimated using the self-controlled case-series method, from databases other than i; 2) same method as 1, but multiplying with background IR; and 3) meta-analyses of observed IRs from databases other than i. IRs for febrile seizures were lower in primary care databases than the hosp

Post-authorisation passive enhanced safety surveillance of seasonal influenza vaccines: Protocol of a pilot study in England

AIM:To pilot enhanced safety surveillance of seasonal influenza vaccine meeting the European Medicines Agency (EMA) requirement to rapidly detect a significant increase in the frequency or severity of adverse events of interest (AEIs), which may indicate risk from the new season's vaccine. STUDY DESIGN:A prospective passive enhanced safety surveillance combining data collection from adverse drug reaction (ADR) cards with automated collection of pseudonymised routinely collected electronic health record (EHR) data. This study builds on a feasibility study carried out at the start of the 2015/2016 influenza season. We will report influenza vaccine exposure and any AEIs reported via ADR card or recorded directly into the EHR, from the commencement of influenza vaccination and ends as specified by EMA (30 November 2016). SETTING:Ten volunteer English general practices, primarily using the GSK influenza vaccines. They had selected this vaccine in advance of the study. PARTICIPANTS:People who receive a seasonal influenza vaccine, in each age group defined in EMA interim guidance: 6 months to 5 years, 6-12 years, 13-17 years, 18-65 years and &gt;65 years. OUTCOME MEASURES:The primary outcome measure is the rate of AEIs occurring within 7 days postvaccination, using passive surveillance of general practitioner (GP) EHR systems enhanced by a card-based ADR reporting system. Extracted data will be presented overall by brand (Fluarix Tetra vs others), by age strata and risk groups. The secondary outcome measure is the vaccine uptake among the subjects registered in the enrolled general practices. ETHICS AND DISSEMINATION:Ethical approval was granted by the Proportionate Review Sub-committee of the North East-Newcastle &amp; North Tyneside 2 on 5 August 2016. The study received approval from the Health Research Authority on 1 September 2016. We will produce an interim analysis within 8 weeks, and an end-of-study report, which will be submitted to peer-reviewed journals

Post-authorisation passive enhanced safety surveillance of seasonal influenza vaccines: Protocol of a pilot study in England

AIM:To pilot enhanced safety surveillance of seasonal influenza vaccine meeting the European Medicines Agency (EMA) requirement to rapidly detect a significant increase in the frequency or severity of adverse events of interest (AEIs), which may indicate risk from the new season's vaccine. STUDY DESIGN:A prospective passive enhanced safety surveillance combining data collection from adverse drug reaction (ADR) cards with automated collection of pseudonymised routinely collected electronic health record (EHR) data. This study builds on a feasibility study carried out at the start of the 2015/2016 influenza season. We will report influenza vaccine exposure and any AEIs reported via ADR card or recorded directly into the EHR, from the commencement of influenza vaccination and ends as specified by EMA (30 November 2016). SETTING:Ten volunteer English general practices, primarily using the GSK influenza vaccines. They had selected this vaccine in advance of the study. PARTICIPANTS:People who receive a seasonal influenza vaccine, in each age group defined in EMA interim guidance: 6 months to 5 years, 6-12 years, 13-17 years, 18-65 years and >65 years. OUTCOME MEASURES:The primary outcome measure is the rate of AEIs occurring within 7 days postvaccination, using passive surveillance of general practitioner (GP) EHR systems enhanced by a card-based ADR reporting system. Extracted data will be presented overall by brand (Fluarix Tetra vs others), by age strata and risk groups. The secondary outcome measure is the vaccine uptake among the subjects registered in the enrolled general practices. ETHICS AND DISSEMINATION:Ethical approval was granted by the Proportionate Review Sub-committee of the North East-Newcastle and North Tyneside 2 on 5 August 2016. The study received approval from the Health Research Authority on 1 September 2016. We will produce an interim analysis within 8 weeks, and an end-of-study report, which will be submitted to peer-reviewed journals

Post-authorisation passive enhanced safety surveillance of seasonal influenza vaccines: protocol of a pilot study in England

Aim To pilot enhanced safety surveillance of seasonal influenza vaccine meeting the European Medicines Agency (EMA) requirement to rapidly detect a significant increase in the frequency or severity of adverse events of interest (AEIs), which may indicate risk from the new season’s vaccine. Study design A prospective passive enhanced safety surveillance combining data collection from adverse drug reaction (ADR) cards with automated collection of pseudonymised routinely collected electronic health record (EHR) data. This study builds on a feasibility study carried out at the start of the 2015/2016 influenza season. We will report influenza vaccine exposure and any AEIs reported via ADR card or recorded directly into the EHR, from the commencement of influenza vaccination and ends as specified by EMA (30 November 2016). Setting Ten volunteer English general practices, primarily using the GSK influenza vaccines. They had selected this vaccine in advance of the study. Participants People who receive a seasonal influenza vaccine, in each age group defined in EMA interim guidance: 6 months to 5 years, 6–12 years, 13–17 years, 18–65 years and >65 years. Outcome measures The primary outcome measure is the rate of AEIs occurring within 7 days postvaccination, using passive surveillance of general practitioner (GP) EHR systems enhanced by a card-based ADR reporting system. Extracted data will be presented overall by brand (Fluarix Tetra vs others), by age strata and risk groups. The secondary outcome measure is the vaccine uptake among the subjects registered in the enrolled general practices.</p

ADVANCE system testing: estimating the incidence of adverse events following pertussis vaccination in healthcare databases with incomplete exposure data

The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public–private collaboration aiming to develop and test a system for rapid vaccine benefit-risk monitoring using existing European healthcare databases. Incidence rate (IR) estimates of vaccination-associated adverse events that are needed to model vaccination risks can be calculated from existing healthcare databases when vaccination (exposure) data are available. We assessed different methods to derive IRs in risk periods following vaccination when exposure data are missing in one database, using estimated IRs and IRRs from other databases for febrile seizures, fever and persistent crying. IRs were estimated for children aged 0–5 years in outcome-specific risk and non-risk periods following the first dose of acellular pertussis (aP) vaccination in four primary care databases and one hospital database. We compared derived and observed IRs in each database using three methods: 1) multiplication of non-risk period IR for database i by IR ratio (IRR) obtained from meta-analysis of IRRs estimated using the self-controlled case-series method, from databases other than i; 2) same method as 1, but multiplying with background IR; and 3) meta-analyses of observed IRs from databases other than i. IRs for febrile seizures were lower in primary care databases than the hospital database. The derived IR for febrile seizures using data from primary care databases was lower than that observed in the hospital database, and using data from the hospital database gave a higher derived IR than that observed in the primary care database. For fever and persistent crying the opposite was observed. We demonstrated that missing IRs for a post-vaccination period can be derived but that the type of database and the method of event data capture can have an impact on potential bias. We recommend IRs are derived using data from similar database types (hospital or primary care) with caution as even this can give heterogeneous results