The Impact of Multiple Sclerosis Disease Status and Subtype on Hematological Profile

Jacob M. Miller, Jeremy T. Beales, Matthew D. Montierth, Farren B. Briggs, Scott F. Frodsham and Mary Feller Davis
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Jacob M. Miller: Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA
Jeremy T. Beales: Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA
Matthew D. Montierth: Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA
Farren B. Briggs: Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
Scott F. Frodsham: Division of Nephrology and Hypertension, University of Utah, Salt Lake City, UT 84112, USA
Mary Feller Davis: Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA

IJERPH, 2021, vol. 18, issue 6, 1-9

Abstract: Multiple sclerosis (MS) is an immune-mediated, demyelinating disease of the central nervous system. In this study, an MS cohort and healthy controls were stratified into Caucasian and African American groups. Patient hematological profiles—composed of complete blood count (CBC) and complete metabolic panel (CMP) test values—were analyzed to identify differences between MS cases and controls and between patients with different MS subtypes. Additionally, random forest models were used to determine the aggregate utility of common hematological tests in determining MS disease status and subtype. The most significant and relevant results were increased bilirubin and creatinine in MS cases. The random forest models achieved some success in differentiating between MS cases and controls (AUC values: 0.725 and 0.710, respectively) but were not successful in differentiating between subtypes. However, larger samples that adjust for possible confounding variables, such as treatment status, may reveal the value of these tests in differentiating between MS subtypes.

Keywords: multiple sclerosis; random forest; electronic health records (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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