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Causality assessment of suspected virustransmission by human plasma products
Author(s) -
Schosser Rudolf,
KellerStanislawski Brigitte,
Nübling C. Micha,
Löwer Johannes
Publication year - 2001
Publication title -
transfusion
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.045
H-Index - 132
eISSN - 1537-2995
pISSN - 0041-1132
DOI - 10.1046/j.1537-2995.2001.41081020.x
Subject(s) - checklist , causality (physics) , computer science , decision tree , pharmacovigilance , transmission (telecommunications) , data mining , algorithm , medicine , biology , adverse effect , paleontology , telecommunications , physics , quantum mechanics
BACKGROUND: Causality assessment of reports on suspected virus transmission is crucial for early detection of infectious plasma products. Commonly used algorithms, such as the WHO criteria, do not meet the specific requirements for causality assessment of suspected virus transmission. STUDY DESIGN AND METHODS: A special algorithm, based on nucleic acid amplification and gene sequencing technology, effectiveness of validated virus‐inactivation methods, empirical data concerning the safety record of the product, and information on batch‐related infection clusters, was developed. The algorithm is focused on laboratory test results or otherwise standardized data, with few clinical data being required. To facilitate practical application, the algorithm has been converted into a graphical decision tree. RESULTS: The feasibility of the algorithm is shown by causality assessment of sample cases. Three cases are presented with the details of each case used in the 12‐question checklist. The answers provided by the checklist led to the causality classification. CONCLUSION: The algorithm is a tool for evaluating reports of suspected virus transmission in a standardized manner. It thus has the potential to improve early signal detection in pharmacovigilance of plasma products by confirmation or exclusion of suspected infectivity in most cases.