title: Models for the red blood cell lifespan.
abstract: The lifespan of red blood cells (RBCs) plays an important role in the study and interpretation of various clinical conditions. Yet, confusion about the meanings of fundamental terms related to cell survival and their quantification still exists in the literature. To address these issues, we started from a compartmental model of RBC populations based on an arbitrary full lifespan distribution, carefully defined the residual lifespan, current age, and excess lifespan of the RBC population, and then derived the distributions of these parameters. For a set of residual survival data from biotin-labeled RBCs, we fit models based on Weibull, gamma, and lognormal distributions, using nonlinear mixed effects modeling and parametric bootstrapping. From the estimated Weibull, gamma, and lognormal parameters we computed the respective population mean full lifespans (95 % confidence interval): 115.60 (109.17-121.66), 116.71 (110.81-122.51), and 116.79 (111.23-122.75) days together with the standard deviations of the full lifespans: 24.77 (20.82-28.81), 24.30 (20.53-28.33), and 24.19 (20.43-27.73). We then estimated the 95th percentiles of the lifespan distributions (a surrogate for the maximum lifespan): 153.95 (150.02-158.36), 159.51 (155.09-164.00), and 160.40 (156.00-165.58) days, the mean current ages (or the mean residual lifespans): 60.45 (58.18-62.85), 60.82 (58.77-63.33), and 57.26 (54.33-60.61) days, and the residual half-lives: 57.97 (54.96-60.90), 58.36 (55.45-61.26), and 58.40 (55.62-61.37) days, for the Weibull, gamma, and lognormal models respectively. Corresponding estimates were obtained for the individual subjects. The three models provide equally excellent goodness-of-fit, reliable estimation, and physiologically plausible values of the directly interpretable RBC survival parameters.
authors.affiliation: Octet Research Inc., 101 Arch St. Suite 1950, Boston, MA, 02110, USA. rajiv@octetresearch.com.
authors.forename: Rajiv P
authors.identifier: 0000-0002-6045-1482
authors.initials: RP
authors.lastname: Shrestha
authors.affiliation: Department of Mathematics & Statistics, University of Massachusetts, Amherst, MA, 01003, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Horowitz
authors.affiliation: Department of Electrical & Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA.
authors.forename: Christopher V
authors.initials: CV
authors.lastname: Hollot
authors.affiliation: Renal and Transplant Associates of New England, Division of Nephrology, Baystate Medical Center, Tufts University School of Medicine, Boston, MA, USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Germain
authors.affiliation: Department of Pediatrics, College of Medicine, The University of Iowa, Iowa City, IA, 52242, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Widness
authors.affiliation: Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA.
authors.forename: Donald M
authors.initials: DM
authors.lastname: Mock
authors.affiliation: Division of Pharmaceutics, College of Pharmacy, The University of Iowa, Iowa City, IA, 52242, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Veng-Pedersen
authors.affiliation: Department of Mechanical & Industrial Engineering, University of Massachusetts, Amherst, MA, 01003, USA.
authors.forename: Yossi
authors.initials: Y
authors.lastname: Chait
mesh_terms: D002470:Cell Survival / Q000502:physiology; D016922:Cellular Senescence / Q000502:physiology*; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D004912:Erythrocytes / Q000502:physiology*; D006801:Humans; D008954:Models, Biological
keywords: Direct and indirect RBC survival models; Mathematical model; RBC lifespan; Survival functions