Fresh blood product manufacture, issue, and use: a chain of diminishing returns?

The available pool of potential blood donors continues to decrease. There are blood component losses all along the chain of production from the recruitment of the donor, attendance and bleeding of the donor, production process, storage of the inventory in the blood center, storage in the hospital or laboratory, selection, and transfusion of the recipient. There is a requirement and potential to improve product availability by better recruitment strategies, production methods, inventory management, and recipient selection. All of these areas of transfusion medicine have been investigated, and some data and options for improving donor/donation utilization are available in the literature. There are also some developing strategies that have the potential to have a positive influence on the availability of blood components. They include the use of blood components that have often been regarded as expensive. Further studies are required to determine if products such as leukoreduced red cells and platelets, unrefrigerated or fresh whole blood, and some recombinant products can conserve large numbers of other components or reduce hospital costs.

Assessing the accuracy of three viral risk models in predicting the outcome of implementing HIV and HCV NAT donor screening in Australia and the implications for future HBV NAT.

BACKGROUND: Risk modeling is now the most practical method of estimating the residual risk of viral transmission in developed countries. One method of assessing the accuracy of a risk model is to measure the observed against the predicted outcome after implementing a new screening method. The primary objective of this paper is to assess the accuracy of three published models in predicting the impact of implementing HIV and HCV NAT in Australia. STUDY DESIGN AND METHODS: Viral screening data on Australian donors for 2000 and 2001 were retrospectively analyzed. The data were applied to the three models to estimate the risk of transmission and predicted NAT yield for HIV, HCV, and HBV. RESULTS: The median risk estimates for the three models were 1 in 3,415,000 for HIV NAT, 1 in 911,000 for HCV NAT, and 1 in 483,000 for HBsAg. The predicted NAT yield for the three models ranged from 0.17 to 0.30 per million donations for HIV, 1.20 to 5.55 for HCV, and 0.47 to 1.01 for HBV. The observed NAT yield was not significantly different from the expected yield with any of the three models for either HIV or HCV. CONCLUSIONS: First, the residual risk in Australian donors is small in comparison with other transfusion complications and comparable to or lower than the risk in US and European nonremunerated donors. Second, mathematical risk modeling has sufficient precision to be used as a predictive tool for risk-benefit assessments of novel screening procedures. Finally, in relation to the case for implementing HBV NAT and/or anti-HBc in Australia, we conclude that at present, there is inadequate information about our donor population to perform an evidence-based risk-benefit analysis.