Causality assessment of suspected virustransmission by human plasma products

  1. Rudolf Schosser,
  2. Brigitte Keller-Stanislawski,
  3. C. Micha Nübling,
  4. Johannes Löwer

Article first published online: 24 NOV 2002

DOI: 10.1046/j.1537-2995.2001.41081020.x

Issue

Transfusion

Transfusion

Volume 41, Issue 8, pages 1020–1029, August 2001

Additional Information

How to Cite

Schosser, R., Keller-Stanislawski, B., Nübling, C. and Löwer, J. (2001), Causality assessment of suspected virustransmission by human plasma products. Transfusion, 41: 1020–1029. doi: 10.1046/j.1537-2995.2001.41081020.x

Author Information

  1. From Medical Affairs, Hyland Immuno Division, Baxter Deutschland GmbH, Heidelberg, Germany; and the Paul Ehrlich Institute, Federal Agency for Sera and Vaccines, Langen, Germany.

*Address reprint requests to: Rudolf Schosser, MD, PhD, Baxter Deutschland GmbH, Im Breitspiel 13, D-69126 Heidelberg, Germany; e-mail: rudolf_schosser@baxter.com.

Publication History

  1. Issue published online: 24 NOV 2002
  2. Article first published online: 24 NOV 2002
  3. Received: 31 February 1999; Revised: 17 February 2001; Accepted: 26 February 2001

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Keywords:

  • GMP = Good Manufacturing Practices;
  • ID50 = median infectious dose;
  • IMIG = IM immunoglobulin;
  • VI/R = virus-inactivation and/or -reduction

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.

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