Risk of SARS-CoV-2 Infection Breakthrough among the Non-Vaccinated and Vaccinated Population in Italy: A Real-World Evidence Study Based on Big Data

Perrella, Alessandro; Bisogno, Massimo; D’Argenzio, Angelo; Trama, Ugo; Coscioni, Enrico; Orlando, Valentina

doi:10.3390/healthcare10061085

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…The continuous pharmacovigilance monitoring is fundamental to collect more information and help to improve the management of these rare but often severe thromboembolic events associated with COVID-19 vaccination. Further, the use of BigData, as SINFONIA in the Campania Region, associated with a machine learning algorithm for data extraction and analysis granted the possibility to have a deeper evaluation and potentially more helpful support in the evaluation of adverse events to drugs including vaccines [33].…”

Section: Discussionmentioning

confidence: 99%

Thromboembolic Events after COVID-19 Vaccination: An Italian Retrospective Real-World Safety Study

Bernardi,

Mascolo,

Sarno

et al. 2023

Vaccines

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Introduction: Real-world safety studies can provide important evidence on the thromboembolic risk associated with COVID-19 vaccines, considering that millions of people have been already vaccinated against COVID-19. In this study, we aimed to estimate the incidence of thromboembolic events after COVID-19 vaccination and to compare the Oxford–AstraZeneca vaccine with other COVID-19 vaccines. Methods: We conducted a retrospective real-world safety study using data from two different data sources: the Italian Pharmacovigilance database (Rete Nazionale di Farmacovigilanza, RNF) and the Campania Region Health system (Sistema INFOrmativo saNità CampanIA, SINFONIA). From the start date of the COVID-19 vaccination campaign (27 December 2021) to 27 September 2022, information on COVID-19 vaccinations and thromboembolic events were extracted from the two databases. The reporting rate (RR) and its 95% confidence interval (95%CI) of thromboembolic events for 10,000 doses was calculated for each COVID-19 vaccine. Moreover, the odds of being vaccinated with the Oxford–AstraZeneca vaccine vs. the other COVID-19 vaccines in cases with thromboembolic events vs. controls without thromboembolic events were computed. Results: A total of 12,692,852 vaccine doses were administered in the Campania Region, of which 6,509,475 (51.28%) were in females and mostly related to the Pfizer-BioNtech vaccine (65.05%), followed by Moderna (24.31%), Oxford–AstraZeneca (9.71%), Janssen (0.91%), and Novavax (0.02%) vaccines. A total of 641 ICSRs with COVID-19 vaccines and vascular events were retrieved from the RNF for the Campania Region, of which 453 (70.67%) were in females. Most ICSRs reported the Pfizer-BioNtech vaccine (65.05%), followed by Oxford–AstraZeneca (9.71%), Moderna (24.31%), and Janssen (0.91%). A total of 2451 events were reported in the ICSRs (3.8 events for ICSRs), of which 292 were thromboembolic events. The higher RRs of thromboembolic events were found with the Oxford–AstraZeneca vaccine (RR: 4.62, 95%CI: 3.50–5.99) and Janssen vaccine (RR: 3.45, 95%CI: 0.94–8.82). Thromboembolic events were associated with a higher likelihood of exposure to the Oxford–AstraZeneca vaccine compared to Pfizer-BioNtech (OR: 6.06; 95%CI: 4.22–8.68) and Moderna vaccines (OR: 6.46; 95%CI: 4.00–10.80). Conclusion: We observed a higher reporting of thromboembolic events with viral-vector-based vaccines (Oxford–AstraZeneca and Janssen) and an increased likelihood of being exposed to the Oxford–AstraZeneca vaccine compared to the mRNA vaccines (Pfizer-BioNtech and Moderna) among thromboembolic cases.

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Section: Discussionmentioning

confidence: 99%

Thromboembolic Events after COVID-19 Vaccination: An Italian Retrospective Real-World Safety Study

Bernardi,

Mascolo,

Sarno

et al. 2023

Vaccines

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“…These results, according to the new COVID-19 wave currently present in Europe and the USA [35], could be considered in the planning of strategies for early interception in frail patients, aiming to treat them as soon as possible with current antiviral and monoclonal antibodies. This could be made possible with the use of Big Data IT platforms and machine learning algorithms for early identification and direction towards treatment in patients positive for COVID-19, as in SINFONIA [34].…”

Section: Discussionmentioning

confidence: 99%

“…quotidianosanita.it/allegati/allegato3418644.pdf, accessed on 11 September 2023). Early recognition of positive patients was made possible according to Campania Region Big-Data SINFONIA [34] and the regional COVID-19 patients early enrolment treatment protocol (https://www.ordinemedicinapoli.it/upload/file/id-0-1657026671-piano%20 regionale%20di%20contrasto%20al%20covid-19%20-%20luglio%202022.pdf, accessed on 11 September 2023).…”

Section: Methodsmentioning

confidence: 99%

Retrospective Analysis of a Real-Life Use of Tixagevimab–Cilgavimab plus SARS-CoV-2 Antivirals for Treatment of COVID-19

Capoluongo,

Mascolo,

Bernardi

et al. 2023

Pharmaceuticals

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Tixagevimab–cilgavimab is effective for the treatment of early COVID-19 in outpatients with risk factors for progression to severe illness, as well as for primary prevention and post-exposure prophylaxis. We aimed to retrospectively evaluate the hospital stay (expressed in days), prognosis, and negativity rate for COVID-19 in patients after treatment with tixagevimab–cilgavimab. We enrolled 42 patients who were nasal swab-positive for SARS-CoV-2 (antigenic and molecular)—both vaccinated and not vaccinated for COVID-19—hospitalized at the first division of the Cotugno Hospital in Naples who had received a single intramuscular dose of tixagevimab–cilgavimab (300 mg/300 mg). All patient candidates for tixagevimab–cilgavimab had immunocompromised immune systems either due to chronic degenerative disorders (Group A: 27 patients) or oncohematological diseases (Group B: 15 patients). Patients enrolled in group A came under our observation after 10 days of clinical symptoms and 5 days after testing positivite for COVID-19, unlike the other patients enrolled in the study. The mean stay in hospital for the patients in Group A was 21 ± 5 days vs. 25 ± 5 days in Group B. Twenty patients tested negative after a median hospitalization stay of 16 days (IQR: 18–15.25); of them, five (25%) patients belonged to group B. Therefore, patients with active hematological malignancy had a lower negativization rate when treated 10 days after the onset of clinical symptoms and five days after their first COVID-19 positive nasal swab.

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“…Recognizing the potential for additional use of RWD and RWE for regulatory and funding purposes, the United States Congress included in the 21st Century Cures legislation (Cures) (Public Law 114–225, 13 December 2016) the direction for Food and Drug Administration (FDA) to develop a program to evaluate the potential use of RWE to support the approval of a new indication of an approved drug or to support or satisfy post-approval study requirements. The potential benefits of leveraging RWD, stored in EHRs and other sources, have become even more evident with the COVID-19 pandemic either by evaluating the efficacy of vaccine, the risk of diabetes following COVID-19 or the course of COVID-19 in patients with lysosomal storage disorders [ 12 , 13 , 14 ].…”

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confidence: 99%

Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers

Magalhães

Dinis-Oliveira

Taveira-Gomes

2022

IJERPH

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Real world data (RWD) and real-world evidence (RWE) plays an increasingly important role in clinical research since scientific knowledge is obtained during routine clinical large-scale practice and not experimentally as occurs in the highly controlled traditional clinical trials. Particularly, the electronic health records (EHRs) are a relevant source of data. Nevertheless, there are also significant challenges in the correct use and interpretation of EHRs data, such as bias, heterogeneity of the population, and missing or non-standardized data formats. Despite the RWD and RWE recognized difficulties, these are easily outweighed by the benefits of ensuring the efficacy, safety, and cost-effectiveness in complement to the gold standards of the randomized controlled trial (RCT), namely by providing a complete picture regarding factors and variables that can guide robust clinical decisions. Their relevance can be even further evident as healthcare units develop more accurate EHRs always in the respect for the privacy of patient data. This editorial is an overview of the RWD and RWE major aspects of the state of the art and supports the Special Issue on “Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers” aimed to explore all the potential and the utility of RWD and RWE in offering insights on diseases in a broad spectrum.

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Risk of SARS-CoV-2 Infection Breakthrough among the Non-Vaccinated and Vaccinated Population in Italy: A Real-World Evidence Study Based on Big Data

Cited by 5 publications

References 18 publications

Thromboembolic Events after COVID-19 Vaccination: An Italian Retrospective Real-World Safety Study

Thromboembolic Events after COVID-19 Vaccination: An Italian Retrospective Real-World Safety Study

Retrospective Analysis of a Real-Life Use of Tixagevimab–Cilgavimab plus SARS-CoV-2 Antivirals for Treatment of COVID-19

Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers

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