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Algorithm Predicts Matched Unrelated Donor Odds

Biol Blood Marrow Transplant; ePub 2017 Dec 26; Davis, et al

An algorithm appears to accurately predict unrelated donor search results after obtaining HLA typing and ancestry, according to a study involving 830 individuals with multiple myeloma. Investigators tested the accuracy of the HapLogic system and a resulting search prognosis patient categorization algorithm in predicting 8/8 HLA-matched unrelated donor likelihood. Among the results:

  • 6 in every 10 patients had 8/8 unrelated donors identified.
  • Search prognosis categories (217 very good, 104 good, 178 fair, 33 poor, 153 very poor, 145 futile) were linked with a noticeable progressive decrease in 8/8 unrelated donor identification and transplantation.
  • Very good and good categories predicted finding and receiving a donor regardless of ancestry.
  • Patients of European ancestry who were in fair or poor categories were more likely than those of non-European ancestry to receive a donor.
  • Patients in the very poor and futile categories had a very high likelihood of finding no donors.

Citation:

Davis E, Davlin S, Cooper C, et al. Validation of an algorithm to predict the likelihood of an 8/8 HLA-matched unrelated donor at search initiation. [Published online ahead of print December 26, 2017]. Biol Blood Marrow Transplant. doi:10.1016/j.bbmt.2017.12.791.