19 research outputs found
Towards an Interoperable Ecosystem of Research Cohort and Real-world Data Catalogues Enabling Multi-center Studies
Objectives : Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. Methods : In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. Results : We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. Conclusions : We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata âcommon data elementsâ using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR
Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management : a PIONEER Analysis Based on Big Data
Funding statement PIONEER is funded through the IMI2 Joint Undertaking and is listed under grant agreement No. 777492. This joint undertaking receives support from the European Unionâs Horizon 2020 research and innovation programme and European Federation of Pharmaceutical Industries and Associations EFPIA. The European Health Data & Evidence Network has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no. 806968. The Joint Undertaking is supported by the European Unionâs Horizon 2020 research and innovation programme and EFPIA, a large association which represents the biopharmaceutical industry in Europe. The views communicated within are those of PIONEER. Neither the IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained hereinPeer reviewe
Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management:A PIONEER Analysis Based on Big Data
Background: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. Objective: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. Design, setting, and participants: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). Outcome measurements and statistical analysis: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. Results and limitations: The most common comorbidities were hypertension (35â73%), obesity (9.2â54%), and type 2 diabetes (11â28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12â25%) and emergency department visits (10â14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. Conclusions: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. Patient summary: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.</p
From Inception to ConcePTION: Genesis of a Network to Support Better Monitoring and Communication of Medication Safety During Pregnancy and Breastfeeding
In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION projectâBuilding an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generationâwith the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and mother-child linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population
Evaluation empirique dâapproches basĂ©es sur les cas pour la gĂ©nĂ©ration dâalertes de pharmacovigilance Ă partir du SystĂšme National des DonnĂ©es de SantĂ© (SNDS)
France has a large nationwide longitudinal database with claims and hospital data, the SystĂšme National des DonnĂ©es de SantĂ© (French National healthcare database â SNDS), which currently covers almost the complete French population, from birth or immigration to death or emigration, and includes all reimbursed medical and paramedical encounters. Since SNDS systematically and prospectively captures drug dispensings, death, and events leading to hospital stays, it has a strong potential for drug assessment in real life settings. Following the worldwide withdrawal of rofecoxib in 2004, several initiatives aiming to develop and evaluate methodologies for drug safety monitoring on healthcare databases emerged. The EU-ADR alliance (Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge) and OMOP (Observational Outcomes Partnership) were respectively launched in Europe and in the Unites-States. These experiments demonstrated the usefulness of pharmacoepidemiological approaches in drug safety signal detection. However the SNDS had never been tested in this scope. The objective of this thesis was to empirically assess 3 case-based designs â case-population, case-control, and self-controlled case series â for drug-safety alert generation in the SNDS, taking as examples two health outcome of interest: upper gastrointestinal bleeding (UGIB) and acute liver injury (ALI).The overall project consisted of 4 main stages: (1) preparation of the data to fit the OMOP common data model and the selection of positive and negative drug controls for each outcome of interest; (2) analysis of the selected drug controls using the 3 case-based designs, testing several design variants (e.g. testing different risk windows, adjustment strategies, etc.); (3) comparison of design variant performances through the calculation of the area under the receiver operating characteristics curve (AUC), the mean square error (MSE) and the coverage probability; (4) the selection of the best design variant and its calibration for each health outcome of interest.Self-controlled case series showed the best performances in both outcomes, ALI and UGIB, with AUCs reaching respectively 0.80 and 0.94 and MSEs 0.07 and 0.12. For UGIB optimal performances were observed when adjusting for multiple drugs and using a risk window corresponding to the 30 first days of exposure. For ALI, optimal performances were also observed when adjusting for multiple drugs but using a risk window corresponding to the overall period covered by drug dispensings. Negative drug control implementation highlighted that a low systematic error seemed to be generated by the optimum variants in the SNDS but that protopathic bias and confounding by indication remained unaddressed issues.These results showed that self-controlled case series were well suited to detect drug safety alerts associated with UGIB and ALI in the SNDS in an accurate manner. A clinical perspective remains necessary to rule out potential false positive signals from residual confounding. The application in routine of such approaches extended to other outcomes of interest could result in substantial progress in pharmacovigilance in France.La France possĂšde une large base de donnĂ©es nationale regroupant les donnĂ©es de liquidation de lâAssurance Maladie, de mortalitĂ© et des donnĂ©es hospitaliĂšres : le SystĂšme National des DonnĂ©es de SantĂ© (SNDS). Celui-ci couvre actuellement la quasi-totalitĂ© de la population française de la naissance (ou immigration), au dĂ©cĂšs (ou Ă©migration), en incluant tous les remboursements de frais mĂ©dicaux ou paramĂ©dicaux. En recueillant de maniĂšre systĂ©matique et prospective les dispensations mĂ©dicamenteuses, les Ă©vĂ©nements hospitaliers et les dĂ©cĂšs, le SNDS est dotĂ© dâun fort potentiel pour lâĂ©valuation du mĂ©dicament en vie rĂ©elle. Suite au retrait mondial du rofecoxib en 2004, de nombreuses initiatives visant au dĂ©veloppement et Ă lâĂ©valuation de mĂ©thodologies adaptĂ©es aux bases de donnĂ©es populationnelles pour la surveillance des risques liĂ©s Ă lâusage du mĂ©dicament ont vu le jour, en particulier le rĂ©seau EU-ADR en Europe (Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge) et OMOP (Observational Outcomes Partnership) aux Ătats-Unis. Ces travaux ont dĂ©montrĂ© lâutilitĂ© des approches pharmaco-Ă©pidĂ©miologiques pour la dĂ©tection de signaux de pharmacovigilance. Cependant, le SNDS nâa jamais Ă©tĂ© testĂ© dans cette optique. Lâobjectif de cette thĂšse Ă©tait dâĂ©valuer de maniĂšre empirique, 3 approches pharmaco Ă©pidĂ©miologiques basĂ©es sur les cas pour la gĂ©nĂ©ration dâalerte(s) de pharmacovigilance dans le SNDS : Ă©tude cas-population, Ă©tude cas-tĂ©moins et sĂ©ries de cas autocontrĂŽlĂ©s. Ces approches ont Ă©tĂ© appliquĂ©es Ă deux Ă©vĂ©nements mĂ©dicaux dâintĂ©rĂȘt rĂ©currents en pharmacovigilance : lâhĂ©morragie digestive haute (UGIB) et lâhĂ©patite aigue (ALI). Le projet a Ă©tĂ© composĂ© de 4 principales Ă©tapes : (1) le formatage des donnĂ©es selon les spĂ©cifications du modĂšle commun de donnĂ©es dâOMOP et la sĂ©lection des mĂ©dicaments tĂ©moins positifs et nĂ©gatifs pour chaque Ă©vĂ©nement d'intĂ©rĂȘt ; (2) lâanalyse des mĂ©dicaments tĂ©moins sĂ©lectionnĂ©s en utilisant les 3 approches basĂ©es sur les cas, en dĂ©clinant chaque approche selon plusieurs variantes (par exemple, en testant diffĂ©rentes fenĂȘtres de risque, stratĂ©gies d'ajustement, etc.) ; (3) la comparaison des performances des variantes selon leur aire sous la courbe ROC (AUC), leur erreur quadratique moyenne (MSE) et leur probabilitĂ© de couverture ; (4) la sĂ©lection de la meilleure variante pour chaque Ă©vĂ©nement dâintĂ©rĂȘt et son Ă©talonnage. Sur les 3 approches Ă©tudiĂ©es, câest la sĂ©rie de cas autocontrĂŽlĂ©s qui a montrĂ© les meilleures performances dans UGIB et ALI avec des AUC respectifs de 0,80 et 0,94 et des MSE de 0,07 et 0,12. Pour UGIB, les performances optimales ont Ă©tĂ© observĂ©es lorsque l'ajustement tenait compte des traitements concomitants et lorsque les 30 premiers jours d'exposition au mĂ©dicament dâintĂ©rĂȘt Ă©taient utilisĂ©s comme fenĂȘtre de risque. Pour ALI, les performances optimales ont Ă©tĂ© Ă©galement obtenues lors de l'ajustement en fonction des traitements concomitants, mais en utilisant une fenĂȘtre de risque correspondant Ă lâensemble de la pĂ©riode couverte par les dispensations de mĂ©dicament dâintĂ©rĂȘt. Lâutilisation de mĂ©dicaments tĂ©moins nĂ©gatifs a montrĂ© que lâerreur systĂ©matique rĂ©sultant de lâapplication de lâapproche et des paramĂštres optimaux dans le SNDS semblait faible, mais que les biais protopathiques et de confusion restaient prĂ©sents. Au total, ces travaux ont montrĂ© que les sĂ©ries de cas autocontrĂŽlĂ©es sont Ă considĂ©rer comme une approche adaptĂ©e Ă la dĂ©tection dâalertes de pharmacovigilance associĂ©es Ă ALI et Ă UGIB dans le SNDS. Un point de vue clinique demeure toutefois nĂ©cessaire pour Ă©carter tout risque de faux positif rĂ©sultant de potentiels biais rĂ©siduels. Lâapplication d'une telle approche Ă d'autres Ă©vĂ©nements d'intĂ©rĂȘt et son utilisation en routine constitueraient des progrĂšs substantiels en matiĂšre de pharmacovigilance en France
Empirical assessment of case-based designs for drug safety alert generation in the French National Healthcare System database (SNDS)
La France possĂšde une large base de donnĂ©es nationale regroupant les donnĂ©es de liquidation de lâAssurance Maladie, de mortalitĂ© et des donnĂ©es hospitaliĂšres : le SystĂšme National des DonnĂ©es de SantĂ© (SNDS). Celui-ci couvre actuellement la quasi-totalitĂ© de la population française de la naissance (ou immigration), au dĂ©cĂšs (ou Ă©migration), en incluant tous les remboursements de frais mĂ©dicaux ou paramĂ©dicaux. En recueillant de maniĂšre systĂ©matique et prospective les dispensations mĂ©dicamenteuses, les Ă©vĂ©nements hospitaliers et les dĂ©cĂšs, le SNDS est dotĂ© dâun fort potentiel pour lâĂ©valuation du mĂ©dicament en vie rĂ©elle. Suite au retrait mondial du rofecoxib en 2004, de nombreuses initiatives visant au dĂ©veloppement et Ă lâĂ©valuation de mĂ©thodologies adaptĂ©es aux bases de donnĂ©es populationnelles pour la surveillance des risques liĂ©s Ă lâusage du mĂ©dicament ont vu le jour, en particulier le rĂ©seau EU-ADR en Europe (Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge) et OMOP (Observational Outcomes Partnership) aux Ătats-Unis. Ces travaux ont dĂ©montrĂ© lâutilitĂ© des approches pharmaco-Ă©pidĂ©miologiques pour la dĂ©tection de signaux de pharmacovigilance. Cependant, le SNDS nâa jamais Ă©tĂ© testĂ© dans cette optique. Lâobjectif de cette thĂšse Ă©tait dâĂ©valuer de maniĂšre empirique, 3 approches pharmaco Ă©pidĂ©miologiques basĂ©es sur les cas pour la gĂ©nĂ©ration dâalerte(s) de pharmacovigilance dans le SNDS : Ă©tude cas-population, Ă©tude cas-tĂ©moins et sĂ©ries de cas autocontrĂŽlĂ©s. Ces approches ont Ă©tĂ© appliquĂ©es Ă deux Ă©vĂ©nements mĂ©dicaux dâintĂ©rĂȘt rĂ©currents en pharmacovigilance : lâhĂ©morragie digestive haute (UGIB) et lâhĂ©patite aigue (ALI). Le projet a Ă©tĂ© composĂ© de 4 principales Ă©tapes : (1) le formatage des donnĂ©es selon les spĂ©cifications du modĂšle commun de donnĂ©es dâOMOP et la sĂ©lection des mĂ©dicaments tĂ©moins positifs et nĂ©gatifs pour chaque Ă©vĂ©nement d'intĂ©rĂȘt ; (2) lâanalyse des mĂ©dicaments tĂ©moins sĂ©lectionnĂ©s en utilisant les 3 approches basĂ©es sur les cas, en dĂ©clinant chaque approche selon plusieurs variantes (par exemple, en testant diffĂ©rentes fenĂȘtres de risque, stratĂ©gies d'ajustement, etc.) ; (3) la comparaison des performances des variantes selon leur aire sous la courbe ROC (AUC), leur erreur quadratique moyenne (MSE) et leur probabilitĂ© de couverture ; (4) la sĂ©lection de la meilleure variante pour chaque Ă©vĂ©nement dâintĂ©rĂȘt et son Ă©talonnage. Sur les 3 approches Ă©tudiĂ©es, câest la sĂ©rie de cas autocontrĂŽlĂ©s qui a montrĂ© les meilleures performances dans UGIB et ALI avec des AUC respectifs de 0,80 et 0,94 et des MSE de 0,07 et 0,12. Pour UGIB, les performances optimales ont Ă©tĂ© observĂ©es lorsque l'ajustement tenait compte des traitements concomitants et lorsque les 30 premiers jours d'exposition au mĂ©dicament dâintĂ©rĂȘt Ă©taient utilisĂ©s comme fenĂȘtre de risque. Pour ALI, les performances optimales ont Ă©tĂ© Ă©galement obtenues lors de l'ajustement en fonction des traitements concomitants, mais en utilisant une fenĂȘtre de risque correspondant Ă lâensemble de la pĂ©riode couverte par les dispensations de mĂ©dicament dâintĂ©rĂȘt. Lâutilisation de mĂ©dicaments tĂ©moins nĂ©gatifs a montrĂ© que lâerreur systĂ©matique rĂ©sultant de lâapplication de lâapproche et des paramĂštres optimaux dans le SNDS semblait faible, mais que les biais protopathiques et de confusion restaient prĂ©sents. Au total, ces travaux ont montrĂ© que les sĂ©ries de cas autocontrĂŽlĂ©es sont Ă considĂ©rer comme une approche adaptĂ©e Ă la dĂ©tection dâalertes de pharmacovigilance associĂ©es Ă ALI et Ă UGIB dans le SNDS. Un point de vue clinique demeure toutefois nĂ©cessaire pour Ă©carter tout risque de faux positif rĂ©sultant de potentiels biais rĂ©siduels. Lâapplication d'une telle approche Ă d'autres Ă©vĂ©nements d'intĂ©rĂȘt et son utilisation en routine constitueraient des progrĂšs substantiels en matiĂšre de pharmacovigilance en France.France has a large nationwide longitudinal database with claims and hospital data, the SystĂšme National des DonnĂ©es de SantĂ© (French National healthcare database â SNDS), which currently covers almost the complete French population, from birth or immigration to death or emigration, and includes all reimbursed medical and paramedical encounters. Since SNDS systematically and prospectively captures drug dispensings, death, and events leading to hospital stays, it has a strong potential for drug assessment in real life settings. Following the worldwide withdrawal of rofecoxib in 2004, several initiatives aiming to develop and evaluate methodologies for drug safety monitoring on healthcare databases emerged. The EU-ADR alliance (Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge) and OMOP (Observational Outcomes Partnership) were respectively launched in Europe and in the Unites-States. These experiments demonstrated the usefulness of pharmacoepidemiological approaches in drug safety signal detection. However the SNDS had never been tested in this scope. The objective of this thesis was to empirically assess 3 case-based designs â case-population, case-control, and self-controlled case series â for drug-safety alert generation in the SNDS, taking as examples two health outcome of interest: upper gastrointestinal bleeding (UGIB) and acute liver injury (ALI).The overall project consisted of 4 main stages: (1) preparation of the data to fit the OMOP common data model and the selection of positive and negative drug controls for each outcome of interest; (2) analysis of the selected drug controls using the 3 case-based designs, testing several design variants (e.g. testing different risk windows, adjustment strategies, etc.); (3) comparison of design variant performances through the calculation of the area under the receiver operating characteristics curve (AUC), the mean square error (MSE) and the coverage probability; (4) the selection of the best design variant and its calibration for each health outcome of interest.Self-controlled case series showed the best performances in both outcomes, ALI and UGIB, with AUCs reaching respectively 0.80 and 0.94 and MSEs 0.07 and 0.12. For UGIB optimal performances were observed when adjusting for multiple drugs and using a risk window corresponding to the 30 first days of exposure. For ALI, optimal performances were also observed when adjusting for multiple drugs but using a risk window corresponding to the overall period covered by drug dispensings. Negative drug control implementation highlighted that a low systematic error seemed to be generated by the optimum variants in the SNDS but that protopathic bias and confounding by indication remained unaddressed issues.These results showed that self-controlled case series were well suited to detect drug safety alerts associated with UGIB and ALI in the SNDS in an accurate manner. A clinical perspective remains necessary to rule out potential false positive signals from residual confounding. The application in routine of such approaches extended to other outcomes of interest could result in substantial progress in pharmacovigilance in France
Frequency and timing of adverse reactions to COVID-19 vaccines; A multi-country cohort event monitoring study
Introduction: During the COVID-19 pandemic, EMA set-up a large-scale cohort event monitoring (CEM) system to estimate incidence rates of patient-reported adverse drug reactions (ADRs) of different COVID-19 vaccines across the participating countries. This study aims to give an up to date and in-depth analysis of the frequency of patient-reported ADRs after the 1st, 2nd, and booster vaccination, to identify potential predictors in developing ADRs and to describe time-to-onset (TTO) and time-to-recovery (TTR) of ADRs. Methods: A CEM study was rolled out in a period ranging from February 2021 to February 2023 across multiple European countries; The Netherlands, Belgium, France, the United Kingdom, Italy, Portugal, Romania, Slovakia and Spain. Analysis consisted of a descriptive analyses of frequencies of COVID-19 vaccine-related ADRs for 1st, 2nd and booster vaccination, analysis of potential predictors in developing ADRs with a generalized linear mixed-effects model, analysis of TTO and TTR of ADRs and a sensitivity analysis for loss to follow-up (L2FU). Results: A total of 29,837 participants completed at least the baseline and the first follow-up questionnaire for 1st and 2nd vaccination and 7,250 participants for the booster. The percentage of participants who reported at least one ADR is 74.32% (95%CI 73.82â74.81). Solicited ADRs, including injection site reactions, are very common across vaccination moments. Potential predictors for these reactions are the brand of vaccine used, the patient's age, sex and prior SARS-CoV-2 infection. The percentage of serious ADRs in the study is low for 1st and 2nd vaccination (0.24%, 95%CI 0.19ââ0.31) and booster (0.26%, 95%CI 0.15, 0.41). The TTO was 14 h (median) for dose 1 and slightly longer for dose 2 and booster dose. TTR is generally also within a few days. The effect of L2FU on estimations of frequency is limited. Conclusion: Despite some limitations due to study design and study-roll out, CEM studies can allow prompt and almost real-time observations of the safety of medications directly from a patient-centered perspective, which can play a crucial role for regulatory bodies during an emergency setting such as the COVID-19 pandemic.</p
Cohort Event Monitoring of Adverse Reactions to COVID-19 Vaccines in Seven European Countries: Pooled Results on First Dose
Introduction: COVID-19 vaccines were rapidly authorised, thus requiring intense post-marketing re-evaluation of their benefit-risk profile. A multi-national European collaboration was established with the aim to prospectively monitor safety of the COVID-19 vaccines through web-based survey of vaccinees. Methods: A prospective cohort event monitoring study was conducted with primary consented data collection in seven European countries. Through the web applications, participants received and completed baseline and up to six follow-up questionnaires on self-reported adverse reactions for at least 6 months following the first dose of COVID-19 vaccine (Netherlands, France, Belgium, UK, Italy) and baseline and up to ten follow-up questionnaires for one year in Germany and Croatia. Rates of adverse reactions have been described by type (solicited, non-solicited; serious/non-serious; and adverse events of special interest) and stratified by vaccine brand. We calculated the frequency of adverse reaction after dose 1 and prior to dose 2 among all vaccinees who completed at least one follow-up questionnaire. Results: Overall, 117,791 participants were included and completed the first questionnaire in addition to the baseline: 88,196 (74.9%) from Germany, 27,588 (23.4%) from Netherlands, 984 (0.8%) from France, 570 (0.5%) from Italy, 326 (0.3%) from Croatia, 89 (0.1%) from the UK and 38 (0.03%) from Belgium. There were 89,377 (75.9%) respondents who had received AstraZeneca vaccines, 14,658 (12.4%) BioNTech/Pfizer, 11,266 (9.6%) Moderna and 2490 (2.1%) Janssen vaccines as a first dose. Median age category was 40-49 years for all vaccines except for Pfizer where median age was 70-79 years. Most vaccinees were female with a female-to-male ratio of 1.34, 1.96 and 2.50 for AstraZeneca, Moderna and Janssen, respectively. BioNtech/Pfizer had slightly more men with a ratio of 0.82. Fatigue and headache were the most commonly reported solicited systemic adverse reactions and injection-site pain was the most common solicited local reaction. The rates of adverse events of special interest (AESIs) were 0.1-0.2% across all vaccine brands. Conclusion: This large-scale prospective study of COVID-19 vaccine recipients showed, for all the studied vaccines, a high frequency of systemic reactions, related to the immunogenic response, and local reactions at the injection site, while serious reactions or AESIs were uncommon, consistent with those reported on product labels. This study demonstrated the feasibility of setting up and conducting cohort event monitoring across multiple European countries to collect safety data on novel vaccines that are rolled out at scale in populations which may not have been included in pivotal trials
Towards an Interoperable Ecosystem of Research Cohort and Real-world Data Catalogues Enabling Multi-center Studies
OBJECTIVES: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. METHODS: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. RESULTS: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. CONCLUSIONS: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR
Safety of COVID-19 Vaccines Among the Paediatric Population: Analysis of the European Surveillance Systems and Pivotal Clinical Trials
Background and objectives: The European Medicine Agency extended the use of Comirnaty, Spikevax, and Nuvaxovid in paediatrics; thus, these vaccines require additional real-world safety evidence. Herein, we aimed to monitor the safety of COVID-19 vaccines through Covid-19 Vaccine Monitor (CVM) and EudraVigilance surveillance systems and the published pivotal clinical trials. Methods: In a prospective cohort of vaccinees aged between 5 and 17 years, we measured the frequency of commonly reported (local/systemic solicited) and serious adverse drug events (ADRs) following the first and second doses of COVID-19 vaccines in Europe using data from the CVM cohort until April 2022. The results of previous pivotal clinical trials and data in the EudraVigilance were also analysed. Results: The CVM study enrolled 658 first-dose vaccinees (children aged 5-11 years; n = 250 and adolescents aged 12-17 years; n = 408). Local/systemic solicited ADRs were common, whereas serious ADRs were uncommon. Among Comirnaty first and second dose recipients, 28.8% and 17.1% of children and 54.2% and 52.2% of adolescents experienced at least one ADR, respectively; injection-site pain (29.2% and 20.7%), fatigue (16.1% and 12.8%), and headache (22.1% and 19.3%) were the most frequent local and systemic ADRs. Results were consistent but slightly lower than in pivotal clinical trials. Reporting rates in Eudravigilance were lower by a factor of 1000. Conclusions: The CVM study showed high frequencies of local solicited reactions after vaccination but lower rates than in pivotal clinical trials. Injection-site pain, fatigue, and headache were the most commonly reported ADRs for clinical trials, but higher than spontaneously reported data