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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