Prediction and impact of personalized donation intervals

Jarkko Toivonen*, Yrjö Koski, Esa Turkulainen, Femmeke Prinsze, Pietro Della Briotta Parolo, Markus Heinonen, Mikko Arvas

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
39 Downloads (Pure)

Abstract

Background and Objectives

Deferral of blood donors due to low haemoglobin (Hb) is demotivating to donors, can be a sign for developing anaemia and incurs costs for blood establishments. The prediction of Hb deferral has been shown to be feasible in a number of studies based on demographic, Hb measurement and donation history data. The aim of this paper is to evaluate how state-of-the-art computational prediction tools can facilitate nationwide personalized donation intervals.

Materials and Methods

Using donation history data from the last 20 years in Finland, FinDonor blood donor cohort data and blood service Biobank genotyping data, we built linear and non-linear predictors of Hb deferral. Based on financial data from the Finnish Red Cross Blood Service, we then estimated the economic impacts of deploying such predictors.

Results

We discovered that while linear predictors generally predict Hb relatively well, they have difficulties in predicting low Hb values. Overall, we found that non-linear or linear predictors with or without genetic data performed only slightly better than a simple cutoff based on previous Hb. However, if any of our deferral prediction methods are used to assign temporary prolongations of donation intervals for females, then our calculations indicate cost savings while maintaining the blood supply.

Conclusion

We find that even though the prediction accuracy is not very high, the actual use of any of our predictors in blood collection is still likely to bring benefits to blood donors and blood establishments alike.
Original languageEnglish
Pages (from-to)504-512
Number of pages9
JournalVOX SANGUINIS
Volume117
Issue number4
Early online date26 Nov 2021
DOIs
Publication statusPublished - Apr 2022
MoE publication typeA1 Journal article-refereed

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