title: Prediction of hemoglobin in blood donors using a latent class mixed-effects transition model.
abstract: Blood donors experience a temporary reduction in their hemoglobin (Hb) value after donation. At each visit, the Hb value is measured, and a too low Hb value leads to a deferral for donation. Because of the recovery process after each donation as well as state dependence and unobserved heterogeneity, longitudinal data of Hb values of blood donors provide unique statistical challenges. To estimate the shape and duration of the recovery process and to predict future Hb values, we employed three models for the Hb value: (i) a mixed-effects models; (ii) a latent-class mixed-effects model; and (iii) a latent-class mixed-effects transition model. In each model, a flexible function was used to model the recovery process after donation. The latent classes identify groups of donors with fast or slow recovery times and donors whose recovery time increases with the number of donations. The transition effect accounts for possible state dependence in the observed data. All models were estimated in a Bayesian way, using data of new entrant donors from the Donor InSight study. Informative priors were used for parameters of the recovery process that were not identified using the observed data, based on results from the clinical literature. The results show that the latent-class mixed-effects transition model fits the data best, which illustrates the importance of modeling state dependence, unobserved heterogeneity, and the recovery process after donation. The estimated recovery time is much longer than the current minimum interval between donations, suggesting that an increase of this interval may be warranted.
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Kazem
authors.initials: K
authors.lastname: Nasserinejad
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Joost
authors.initials: J
authors.lastname: van Rosmalen
authors.affiliation: Department of Donor Studies, Sanquin Research, Amsterdam, the Netherlands.|Department of Public Health, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Wim
authors.initials: W
authors.lastname: de Kort
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Dimitris
authors.identifier: http://orcid.org/0000-0001-9397-0900
authors.initials: D
authors.lastname: Rizopoulos
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.|L-Biostat, KU Leuven, Leuven, Belgium.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Lesaffre
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D001771:Blood Banks / Q000592:standards; D001782:Blood Donors / Q000706:statistics & numerical data*; D046148:Donor Selection; D005260:Female; D006454:Hemoglobins / Q000032:analysis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009426:Netherlands; D011237:Predictive Value of Tests; D012621:Seasons; D012737:Sex Factors
chemical_list: D006454:Hemoglobins
keywords: blood donation; change point model; latent class; mixed-effects model; transition model