UNLABELLED: Adverse events following immunization (AEFI) reported to the national Vaccine Adverse Event Reporting System (VAERS) represent true causally related events, as well as events that are temporally, but not necessarily causally related to vaccine. OBJECTIVE: We sought to determine if the causal relationships between the vaccine and the AEFI reported to VAERS could be assessed through expert review. DESIGN: A stratified random sample of 100 VAERS reports received in 2004 contained 13 fatal cases, 19 cases with non-fatal disabilities, 39 other serious non-fatal cases and 29 non-serious cases. Experts knowledgeable about vaccines and clinical outcomes, reviewed each VAERS report and available medical records. MAIN OUTCOME MEASURES: Modified World Health Organization criteria were used to classify the causal relationship between vaccines and AEFI as definite, probable, possible, unlikely or unrelated. Five independent reviewers evaluated each report. If they did not reach a majority agreement on causality after initial review, the report was discussed on a telephone conference to achieve agreement. RESULTS: 108 AEFIs were identified in the selected 100 VAERS reports. After initial review majority agreement was achieved for 83% of the AEFI and 17% required further discussion. In the end, only 3 (3%) of the AEFI were classified as definitely causally related to vaccine received. Of the remaining AEFI 22 (20%) were classified as probably and 22 (20%) were classified as possibly related to vaccine received; a majority (53%) were classified as either unlikely or unrelated to a vaccine received. CONCLUSIONS: Using VAERS reports and additional documentation, causality could be assessed by expert review in the majority of VAERS reports. Assessment of VAERS reports identified that causality was thought to be probable or definite in less than one quarter of reports, and these were dominated by local reactions, allergic reactions, or symptoms known to be associated with the vaccine administered.
UNLABELLED: Adverse events following immunization (AEFI) reported to the national Vaccine Adverse Event Reporting System (VAERS) represent true causally related events, as well as events that are temporally, but not necessarily causally related to vaccine. OBJECTIVE: We sought to determine if the causal relationships between the vaccine and the AEFI reported to VAERS could be assessed through expert review. DESIGN: A stratified random sample of 100 VAERS reports received in 2004 contained 13 fatal cases, 19 cases with non-fatal disabilities, 39 other serious non-fatal cases and 29 non-serious cases. Experts knowledgeable about vaccines and clinical outcomes, reviewed each VAERS report and available medical records. MAIN OUTCOME MEASURES: Modified World Health Organization criteria were used to classify the causal relationship between vaccines and AEFI as definite, probable, possible, unlikely or unrelated. Five independent reviewers evaluated each report. If they did not reach a majority agreement on causality after initial review, the report was discussed on a telephone conference to achieve agreement. RESULTS: 108 AEFIs were identified in the selected 100 VAERS reports. After initial review majority agreement was achieved for 83% of the AEFI and 17% required further discussion. In the end, only 3 (3%) of the AEFI were classified as definitely causally related to vaccine received. Of the remaining AEFI 22 (20%) were classified as probably and 22 (20%) were classified as possibly related to vaccine received; a majority (53%) were classified as either unlikely or unrelated to a vaccine received. CONCLUSIONS: Using VAERS reports and additional documentation, causality could be assessed by expert review in the majority of VAERS reports. Assessment of VAERS reports identified that causality was thought to be probable or definite in less than one quarter of reports, and these were dominated by local reactions, allergic reactions, or symptoms known to be associated with the vaccine administered.
Authors: P Pellegrino; F S Falvella; V Perrone; C Carnovale; T Brusadelli; M Pozzi; S Antoniazzi; S Cheli; C Perrotta; E Clementi; S Radice Journal: Pharmacogenomics J Date: 2014-10-07 Impact factor: 3.550
Authors: Cosby A Stone; Christine R F Rukasin; Thomas M Beachkofsky; Elizabeth J Phillips Journal: Br J Clin Pharmacol Date: 2019-11-05 Impact factor: 4.335
Authors: Ana Cristina Vanderley Oliveira; Licia Maria Henrique da Mota; Leopoldo Luiz Dos Santos-Neto; Jozélio Freire De Carvalho; Iramaya Rodrigues Caldas; Olindo Assis Martins Filho; Pedro Luis Tauil Journal: Autoimmune Dis Date: 2014-10-22