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Multiple hematological biomarkers (i.e. complete blood counts and serum chemistry parameters) were used in a multivariate linear-regression fit to create predictive algorithms for estimating the severity of hematopoietic acute radiation syndrome (H-ARS) using two different species (i.e. Göttingen Minipig and non-human primate (NHP) (Macacca mulatta)). Biomarker data were analyzed prior to irradiation and between 1-60 days (minipig) and 1-30 days (NHP) after irradiation exposures of 1.6-3.5 Gy (minipig) and 6.5 Gy (NHP) 60 Co gamma ray doses at 0.5-0.6 Gy min -1 and 0.4 Gy min -1 , respectively. Fitted radiation risk and injury categorization (RRIC) values and RRIC prediction percent accuracies were compared between the two models. Both models estimated H-ARS severity with over 80% overall predictive power and with receiver operating characteristic curve area values of 0.884 and 0.825. These results based on two animal radiation models support the concept for the use of a hematopoietic-based algorithm for predicting the risk of H-ARS in humans.

MODELING H-ARS USING HEMATOLOGICAL PARAMETERS: A COMPARISON BETWEEN THE NON-HUMAN PRIMATE AND MINIPIG