Why we need more collaboration in Europe to enhance post-marketing surveillance of vaccines

Effectiveness and safety of recombinant zoster vaccine: A review of real-world evidence

The recombinant zoster vaccine (RZV) was licensed in the US for prevention of herpes zoster (HZ) in 2017. We conducted a literature search (January 1, 2017-August 1, 2023) using PubMed, Embase, and Scopus to consolidate the real-world evidence related to RZV. Overall, RZV effectiveness against HZ was high across the studied populations in real-world settings, including adults aged ≥ 50 years and patients aged ≥ 18 years with immunodeficiency or immunosuppression. Effectiveness was higher with two doses versus one dose, especially in elderly people and immunocompromised individuals. The safety profile of RZV was broadly consistent with that established in clinical trials. RZV does not appear to increase the risk of disease flares in patients with immune-mediated diseases. Approximately two-thirds of individuals received a second RZV dose within 2-6 months after the first dose. Collectively, RZV effectiveness against HZ was high, and these real-world studies reaffirm its favorable benefit-risk profile.

Three seasons of enhanced safety surveillance of a cell culture-based quadrivalent influenza vaccine

The objective of this paper is to summarize annual enhanced safety surveillance activity across three seasons (2019/20-2021/22) for cell culture-based quadrivalent influenza vaccine (QIVc; Flucelvax® Tetra) in all age groups. This activity was conducted in primary care setting in Genoa (Italy) during the seasons 2019/20, 2020/21 and 2021/22. All adverse events registered within the first seven days following immunization were analyzed by season, type, age group and seriousness. Over three seasons, 3,603 QIVc exposures were recorded within the enhanced passive safety surveillance activity. No safety signals were identified. The overall reporting rates of individual case safety reports for the seasons 2019/20, 2020/21 and 2021/22 were 1.75%, 0.48% and 0.40%, respectively. The average number of adverse events per individual case safety report was similar (range 3.3-3.8 adverse events per case report) across the three seasons. Most adverse events were reactogenic in nature. The rate of adverse events was similarly low in all age groups. Enhanced passive safety surveillance activity is a feasible approach for the post-marketing monitoring of seasonal influenza vaccines. Within its limitations, results of this study support the favorable safety profile of QIVc. These safety data could further bolster public trust in influenza vaccines with the goal to increase vaccination uptake in all target groups.

The readiness of the spontaneous reporting system for COVID-19 vaccines safety monitoring in Croatia

We aimed to identify whether a spontaneous reporting system (SRS) in Croatia could timely identify and confirm signals for COVID-19 vaccines. Post-marketing spontaneous reports of adverse drug reactions (ADRs) following COVID-19 immunisation reported to the Agency for Medicinal Products and Medical Devices of Croatia (HALMED) were extracted and analysed. 6624 cases reporting 30 655 ADRs following COVID-19 immunisation were received from 27^th December 2020 to 31st December 2021. Available data in those cases were compared with data available to the EU network at the time when signals were confirmed and minimisation measures were implemented. 5032 cases, reporting 22 524 ADRs, were assessed as non-serious, and 1,592 cases, reporting 8,131 ADRs as serious. The most reported serious ADRs, which were listed in the MedDRA Important medical events terms list, were syncope (n = 58), arrhythmia (n = 48), pulmonary embolism (n = 45), loss of consciousness (n = 43), and deep vein thrombosis (n = 36). The highest reporting rate had Vaxzevria (0.003), followed by Spikevax and Jcovden (0.002), and Comirnaty (0.001). Potential signals were identified, however, they couldn't be timely confirmed solely on cases retrieved by SRS. In order to overcome the limitations of SRS, active surveillance and post-authorisation safety studies of vaccines should be implemented in Croatia.

ICD-11: A catalyst for advancing patient safety surveillance globally

The World Health Organization's (WHO) international classification of disease version 11 (ICD-11) contains several features which enable improved classification of patient safety events. We have identified three suggestions to facilitate adoption of ICD-11 from the patient safety perspective. One, health system leaders at national, regional, and local levels should incorporate ICD-11 into all approaches to monitor patient safety. This will allow them to take advantage of the innovative patient safety classification methods embedded in ICD-11 to overcome several limitations related to existing patient safety surveillance methods. Two, application developers should incorporate ICD-11 into software solutions. This will accelerate adoption and utility of software-enabled clinical and administrative workflows relevant to patient safety management. This is enabled as a result of the ICD-11 application programming interface (or API) developed by the WHO. Third, health system leaders should adopt the ICD-11 using a continuous improvement framework. This will help leaders at national, regional and local levels to take advantage of specific existing initiatives which will be strengthened by ICD-11, including peer review comparisons, clinician engagement, and alignment of front-line safety efforts with post marketing surveillance of medical technologies. While the investment to adopt ICD-11 will be considerable, these will be offset by reducing the ongoing costs related to a lack of accurate routine information.

Background rates of 41 adverse events of special interest for COVID-19 vaccines in 10 European healthcare databases - an ACCESS cohort study

BACKGROUND

In May 2020, the ACCESS (The vACCine covid-19 monitoring readinESS) project was launched to prepare real-world monitoring of COVID-19 vaccines. Within this project, this study aimed to generate background incidence rates of 41 adverse events of special interest (AESI) to contextualize potential safety signals detected following administration of COVID-19 vaccines.

METHODS

A dynamic cohort study was conducted using a distributed data network of 10 healthcare databases from 7 European countries (Italy, Spain, Denmark, The Netherlands, Germany, France and United Kingdom) over the period 2017 to 2020. A common protocol (EUPAS37273), common data model, and common analytics programs were applied for syntactic, semantic and analytical harmonization. Incidence rates (IR) for each AESI and each database were calculated by age and sex by dividing the number of incident cases by the total person-time at risk. Age-standardized rates were pooled using random effect models according to the provenance of the events.

FINDINGS

A total number of 63,456,074 individuals were included in the study, contributing to 211.7 million person-years. A clear age pattern was observed for most AESIs, rates also varied by provenance of disease diagnosis (primary care, specialist care). Thrombosis with thrombocytopenia rates were extremely low ranging from 0.06 to 4.53/100,000 person-years for cerebral venous sinus thrombosis (CVST) with thrombocytopenia (TP) and mixed venous and arterial thrombosis with TP, respectively.

INTERPRETATION

Given the nature of the AESIs and the setting (general practitioners or hospital-based databases or both), background rates from databases that show the highest level of completeness (primary care and specialist care) should be preferred, others can be used for sensitivity. The study was designed to ensure representativeness to the European population and generalizability of the background incidence rates.

FUNDING

The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE.

The value of public-private collaborative real-world evidence platforms to monitor vaccine performance post authorization: DRIVE - a European initiative

INTRODUCTION

Fighting pandemics requires an established infrastructure for pandemic preparedness, with existing, sustainable platforms ready to be activated. This includes platforms for disease surveillance, virus circulation, and vaccine performance monitoring based on Real-World data, to complement clinical trial evidence.

AREAS COVERED

Because of its complexity, this can best be done by combining efforts between public and private sectors, developing a multi-stakeholder approach. Public-Private-Partnerships increasingly play a critical role in combating infectious diseases but are still looked at with hesitancy. The Development of Robust and Innovative Vaccine Effectiveness (DRIVE) project, which established a platform for measuring brand-specific influenza vaccine effectiveness in Europe, exemplifies how to build a collaborative platform with transparent governance, state-of-the-art methodology, and a large network of participating sites. Lessons learned from DRIVE have been cardinal to set up COVIDRIVE, a platform for brand-specific COVID-19 vaccine effectiveness monitoring.

EXPERT OPINION

The DRIVE partners propose that a debate on the benefits of Public-Private-Partnership-generated real-world evidence for vaccine effectiveness monitoring should be pursued to clarify roles and responsibilities, set up expectations, and decide the future environment for vaccine monitoring in Europe. In parallel, the driving factors behind PPP hesitancy should be studied.

Postmarketing studies: can they provide a safety net for COVID-19 vaccines in the UK?

In the current era of the COVID-19 pandemic, the world has never been more interested in the process of vaccine development. While researchers across the globe race to find an effective yet safe vaccine to protect populations from the newly emergent SARS-CoV-2 virus, more than one-third of the world has been subjected to either full or partial lockdown measures. With communities having felt the burden of prolonged isolation, finding a safe and efficacious vaccine will yield direct beneficial effects on protecting against COVID-19 morbidity and mortality and help relieve the psychological and economic load on communities living with COVID-19. There is hope that with the extraordinary efforts of scientists a vaccine will become available. However, given the global public health crisis, development of a COVID-19 vaccine will need to be fast tracked through the usual prelicensing development stages and introduced with limited clinical trial data compared with those vaccines that are developed conventionally over more than a decade. In this scenario, surveillance of the vaccine in the real world becomes even more paramount. This responsibility falls to observational researchers who can provide an essential safety net by continuing to monitor the effectiveness and safety of a COVID-19 vaccine after licensing. Postauthorisation observational studies for safety and effectiveness are complementary to prelaunch clinical trials and not a replacement. In this paper, we highlight the importance of postmarketing studies for future newly licensed COVID-19 vaccines and the key epidemiological considerations.

The Food and Drug Administration Biologics Effectiveness and Safety Initiative Facilitates Detection of Vaccine Administrations From Unstructured Data in Medical Records Through Natural Language Processing

Introduction: The Food and Drug Administration Center for Biologics Evaluation and Research conducts post-market surveillance of biologic products to ensure their safety and effectiveness. Studies have found that common vaccine exposures may be missing from structured data elements of electronic health records (EHRs), instead being captured in clinical notes. This impacts monitoring of adverse events following immunizations (AEFIs). For example, COVID-19 vaccines have been regularly administered outside of traditional medical settings. We developed a natural language processing (NLP) algorithm to mine unstructured clinical notes for vaccinations not captured in structured EHR data.

Methods: A random sample of 1,000 influenza vaccine administrations, representing 995 unique patients, was extracted from a large U.S. EHR database. NLP techniques were used to detect administrations from the clinical notes in the training dataset [80% (N = 797) of patients]. The algorithm was applied to the validation dataset [20% (N = 198) of patients] to assess performance. Full medical charts for 28 randomly selected administration events in the validation dataset were reviewed by clinicians. The NLP algorithm was then applied across the entire dataset (N = 995) to quantify the number of additional events identified.

Results: A total of 3,199 administrations were identified in the structured data and clinical notes combined. Of these, 2,740 (85.7%) were identified in the structured data, while the NLP algorithm identified 1,183 (37.0%) administrations in clinical notes; 459 were not also captured in the structured data. This represents a 16.8% increase in the identification of vaccine administrations compared to using structured data alone. The validation of 28 vaccine administrations confirmed 27 (96.4%) as “definite” vaccine administrations; 18 (64.3%) had evidence of a vaccination event in the structured data, while 10 (35.7%) were found solely in the unstructured notes.

Discussion: We demonstrated the utility of an NLP algorithm to identify vaccine administrations not captured in structured EHR data. NLP techniques have the potential to improve detection of vaccine administrations not otherwise reported without increasing the analysis burden on physicians or practitioners. Future applications could include refining estimates of vaccine coverage and detecting other exposures, population characteristics, and outcomes not reliably captured in structured EHR data.

Methodological frontiers in vaccine safety: qualifying available evidence for rare events, use of distributed data networks to monitor vaccine safety issues, and monitoring the safety of pregnancy interventions

While vaccines are rigorously tested for safety and efficacy in clinical trials, these trials do not include enough subjects to detect rare adverse events, and they generally exclude special populations such as pregnant women. It is therefore necessary to conduct postmarketing vaccine safety assessments using observational data sources. The study of rare events has been enabled in through large linked databases and distributed data networks, in combination with development of case-centred methods. Distributed data networks necessitate common protocols, definitions, data models and analytics and the processes of developing and employing these tools are rapidly evolving. Assessment of vaccine safety in pregnancy is complicated by physiological changes, the challenges of mother-child linkage and the need for long-term infant follow-up. Potential sources of bias including differential access to and utilisation of antenatal care, immortal time bias, seasonal timing of pregnancy and unmeasured determinants of pregnancy outcomes have yet to be fully explored. Available tools for assessment of evidence generated in postmarketing studies may downgrade evidence from observational data and prioritise evidence from randomised controlled trials. However, real-world evidence based on real-world data is increasingly being used for safety assessments, and new tools for evaluating real-world evidence have been developed. The future of vaccine safety surveillance, particularly for rare events and in special populations, comprises the use of big data in single countries as well as in collaborative networks. This move towards the use of real-world data requires continued development of methodologies to generate and assess real world evidence.

Incidence Rates of Autoimmune Diseases in European Healthcare Databases: A Contribution of the ADVANCE Project

INTRODUCTION

The public-private ADVANCE collaboration developed and tested a system to generate evidence on vaccine benefits and risks using European electronic healthcare databases. In the safety of vaccines, background incidence rates are key to allow proper monitoring and assessment. The goals of this study were to compute age-, sex-, and calendar-year stratified incidence rates of nine autoimmune diseases in seven European healthcare databases from four countries and to assess validity by comparing with published data.

METHODS

Event rates were calculated for the following outcomes: acute disseminated encephalomyelitis, Bell's palsy, Guillain-Barré syndrome, immune thrombocytopenia purpura, Kawasaki disease, optic neuritis, narcolepsy, systemic lupus erythematosus, and transverse myelitis. Cases were identified by diagnosis codes. Participating organizations/databases originated from Denmark, Italy, Spain, and the UK. The source population comprised all persons registered, with at least 1 year of data prior to the study start, or follow-up from birth. Stratified incidence rates were computed per database over the period 2003 to 2014.

RESULTS

Between 2003 and 2014, 148,947 incident cases of nine autoimmune diseases were identified. Crude incidence rates were highest for Bell's palsy [23.8/100,000 person-years (PYs), 95% confidence interval (CI) 23.6-24.1] and lowest for Kawasaki disease (0.7/100,000 PYs, 95% CI 0.6-0.7). Specific patterns were observed by sex, age, calendar time, and data sources. Rates were comparable with published estimates.

CONCLUSION

A range of autoimmune events could be identified in the ADVANCE system. Estimation of rates indicated consistency across selected European healthcare databases, as well as consistency with US published data.

ADVANCE database characterisation and fit for purpose assessment for multi-country studies on the coverage, benefits and risks of pertussis vaccinations

INTRODUCTION

The public-private ADVANCE consortium (Accelerated development of vaccine benefit-risk collaboration in Europe) aimed to assess if electronic healthcare databases can provide fit-for purpose data for collaborative, distributed studies and monitoring of vaccine coverage, benefits and risks of vaccines.

OBJECTIVE

To evaluate if European healthcare databases can be used to estimate vaccine coverage, benefit and/or risk using pertussis-containing vaccines as an example.

METHODS

Characterisation was conducted using open-source Java-based (Jerboa) software and R scripts. We obtained: (i) The general characteristics of the database and data source (meta-data) and (ii) a detailed description of the database population (size, representatively of age/sex of national population, rounding of birth dates, delay between birth and database entry), vaccinations (number of vaccine doses, recording of doses, pattern of doses by age and coverage) and events of interest (diagnosis codes, incidence rates). A total of nine databases (primary care, regional/national record linkage) provided data on events (pertussis, pneumonia, death, fever, convulsions, injection site reactions, hypotonic hypo-responsive episode, persistent crying) and vaccines (acellular pertussis and whole cell pertussis) related to the pertussis proof of concept studies.

RESULTS

The databases contained data for a total population of 44 million individuals. Seven databases had recorded doses of vaccines. The pertussis coverage estimates were similar to those reported by the World Health Organisation (WHO). Incidence rates of events were comparable in magnitude and age-distribution between databases with the same characteristics. Several conditions (persistent crying and somnolence) were not captured by the databases for which outcomes were restricted to hospital discharge diagnoses.

CONCLUSION

The database characterisation programs and workflows allowed for an efficient, transparent and standardised description and verification of electronic healthcare databases which may participate in pertussis vaccine coverage, benefit and risk studies. This approach is ready to be used for other vaccines/events to create readiness for participation in other vaccine related studies.

ADVANCE system testing: Benefit-risk analysis of a marketed vaccine using multi-criteria decision analysis and individual-level state transition modelling

BACKGROUND

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 benefit-risk (B/R) monitoring of vaccines using electronic health record (eHR) databases in Europe. Proof-of-concept studies were designed to assess the proposed processes and system for generating the required evidence to perform B/R assessment and near-real time monitoring of vaccines. We aimed to test B/R methodologies for vaccines, using the comparison of the B/R profiles of whole-cell (wP) and acellular pertussis (aP) vaccine formulations in children as an example.

METHODS

We used multi-criteria decision analysis (MCDA) to structure the B/R assessment combined with individual-level state transition modelling to build the B/R effects table. In the state transition model, we simulated the number of events in two hypothetical cohorts of 1 million children followed from first pertussis dose till pre-school-entry booster (or six years of age, whichever occurred first), with one cohort receiving wP, and the other aP. The benefits were reductions in pertussis incidence and complications. The risks were increased incidences of febrile convulsions, fever, hypotonic-hyporesponsive episodes, injection-site reactions and persistent crying. Most model parameters were informed by estimates (coverage, background incidences, relative risks) from eHR databases from Denmark (SSI), Spain (BIFAP and SIDIAP), Italy (Pedianet) and the UK (RCGP-RSC and THIN). Preferences were elicited from clinical and epidemiological experts.

RESULTS

Using state transition modelling to build the B/R effects table facilitated the comparison of different vaccine effects (e.g. immediate vaccine risks vs long-term vaccine benefits). Estimates from eHR databases could be used to inform the simulation model. The model results could be easily combined with preference weights to obtain B/R scores.

CONCLUSION

Existing B/R methodology, modelling and estimates from eHR databases can be successfully used for B/R assessment of vaccines.

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.