(A-338) Evaluating the Diagnostic Accuracy of Adverse Events of Special Interest Following Janssen COVID-19 Vaccine (JCOVDEN) Using the VAC4EU Validation Pipeline

Sunday, August 24, 2025

12:00 PM - 1:30 PM ET

Presenting Author(s)

EP

Elena Palà, PhD

Teamit Institute, Spain

Co-Author(s)

AD

Amirreza Dehgahn Tarazjani

Department of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands, Netherlands
OR

Oisin Ryan

Assistant Professor, University Medical Center Utrecht, Utrecht, the Netherlands, Netherlands
AC

Albert Cid Royo

Department of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands, Netherlands
Estel Plana, MSc

Director Biostatistician
Pharmacoepidemiology and Risk Management, RTI Health Solutions, Barcelona, Spain, Spain
CB

Carlo Alberto Bissacco

Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, Spain
Katica Boric, PhD, MSc

Epidemiology Project Manager
RTI Health Solutions, Barcelona, Spain
Barcelona, Catalonia, Spain
AB

Anna Brutau, PhD

TeamIT, Spain
JC

Juan José Carreras Martínez

Vaccine Research Department, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO-Public Health), Valencia, Spain, Spain
EC

Elisa Correcher Martínez

Vaccine Research Department, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO-Public Health), Valencia, Spain, Spain
RG

Raquel Garcia-Esteban

RTI Health Solutions, Barcelona, Spain, Spain
JG

Jordy Gaspersz

PHARMO Institute for Drug Outcomes Research, Utrecht, The Netherlands, Netherlands
MH

María Herrero-Silvestre

Vaccine Research Department, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO - Public Health)
Valencia, Comunidad Valenciana, Spain
MH

Margaret Haugh

UMC Utrecht, France
TL

Thom Lysen

PHARMO Institute for Drug Outcomes Research, Utrecht, The Netherlands, Netherlands
SM

Sima Mohammadi, MD

VAC4EU, Netherlands
JO

Jetty Overbeek

PHARMO Institute for Drug Outcomes Research, Utrecht, The Netherlands, Netherlands
JR

Judit Riera Arnau, MD

UMC utrecht, Spain
AU

Arantxa Urchueguía

Vaccine Research Department, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO-Public Health), Valencia, Spain, Spain
Felipe Villalobos

Primary care researcher
Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, Spain
NP

Nicolas Praet

Johnson & Johnson, Belgium
CW

Corinne Williams, PhD

Jansson & Jansson, France
FA

Fariba Ahmadizar, PharmD, PhD

Data science and biostatistics department, Julius Global Health, University Medical Center Utrecht, Utrecht, The Netherlands, Netherlands
MS

Miriam C.J. Sturkenboom

Department of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands, Netherlands
Joan Fortuny, MD PhD

Senior Director Epidemiology
RTI Health Solutions
Barcelona, Catalonia, Spain

Background: Adverse events of special interest (AESI) are assessed in post-authorization safety studies (PASS) using real-world data (RWD), but the accuracy of codes and algorithms to identify them require validation according to the regulatory guidance for RWD studies.

Objectives: To estimate the positive predictive value (PPV) of diagnostic algorithms for 11 prespecified AESIs across neurological, hematological/thrombotic, and cardiovascular disorders in a retrospective PASS of JCOVDEN in the European Union.

Methods: Case validation was conducted using the VAC4EU framework for defining, ascertaining, and validating AESIs. This was carried out across two data sources (VID, SIDIAP) by trained abstractors using electronic medical records and REDCap questionnaires. We validated up to 50 cases for JCOVDEN and 30 for comparators for each AESI. Cases were assigned a level of diagnostic certainty (LOC) ranging from 1 (definite case) to 5 (definite alternative diagnosis) using adapted Brighton Collaboration case definitions. For each AESI, the PPVs with 95% confidence intervals (CIs) were calculated by dividing the number of confirmed cases (those with a LOC 1-3) by the total number of validated cases (LOC 1, 2, 3, 4a, or 5).

Results: Among JCOVDEN vaccinees, 324 events were validated. The PPV (95%CI) for thrombosis with thrombocytopenia syndrome was 55.2% (35.7–73.6%) in SIDIAP and 100% (2.5–100%) in VID . The PPV of cerebral venous sinus thrombosis was 100% in both data sources. The other AESIs were validated only in VID. High PPVs (above 80%) were observed for cardiac inflammatory disorder (PPV = 83.3% (62.6–95.3%); pulmonary embolism (PPV = 83.3% (67.2–93.6%); hemorrhagic stroke, (PPV = 85.7% (67.3–96.0%). Moderate PPVs (60-75%) were observed for immune thrombocytopenia, PPV = 75.0% (34.9-96.8%); non-hemorrhagic stroke, PPV = 72.4% (52.8–87.3%); transverse myelitis, PPV = 66.7% (9.4-99.1%); Guillain-Barré syndrome, PPV = 62.5% (24.5–91.5%); and deep vein thrombosis, PPV = 60.0% (42.1-76.1%). The PPV for encephalitis was low, PPV = 26.7% (7.8-55.1%).

Conclusions: Levels of diagnostic certainty and PPVs varied across AESIs. The validation approach was effective but limited by available clinical data, highlighting the need for robust data in vaccine safety monitoring.