title: Predicting hemoglobin levels in whole blood donors using transition models and mixed effects models.
abstract: BACKGROUND
  To optimize the planning of blood donations but also to continue motivating the volunteers it is important to streamline the practical organization of the timing of donations. While donors are asked to return for donation after a suitable period, still a relevant proportion of blood donors is deferred from donation each year due to a too low hemoglobin level. Rejection of donation may demotivate the candidate donor and implies an inefficient planning of the donation process. Hence, it is important to predict the future hemoglobin level to improve the planning of donors' visits to the blood bank.
  
  
  METHODS
  The development of the hemoglobin prediction rule is based on longitudinal (panel) data from blood donations collected by Sanquin (the only blood product collecting and supplying organization in the Netherlands). We explored and contrasted two popular statistical models, i.e. the transition (autoregressive) model and the mixed effects model as plausible models to account for the dependence among subsequent hemoglobin levels within a donor.
  
  
  RESULTS
  The predictors of the future hemoglobin level are age, season, hemoglobin levels at the previous visits, and a binary variable indicating whether a donation was made at the previous visit. Based on cross-validation, the areas under the receiver operating characteristic curve (AUCs) for male donors are 0.83 and 0.81 for the transition model and the mixed effects model, respectively; for female donors we obtained AUC values of 0.73 and 0.72 for the transition model and the mixed effects model, respectively.
  
  
  CONCLUSIONS
  We showed that the transition models and the mixed effects models provide a much better prediction compared to a multiple linear regression model. In general, the transition model provides a somewhat better prediction than the mixed effects model, especially at high visit numbers. In addition, the transition model offers a better trade-off between sensitivity and specificity when varying the cut-off values for eligibility in predicted values. Hence transition models make the prediction of hemoglobin level more precise and may lead to less deferral from donation in the future.
authors: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands. k.nasserinejad@erasmusmc.nl
authors: Kazem
authors: K
authors: Nasserinejad
authors: Wim
authors: W
authors: de Kort
authors: Mireille
authors: M
authors: Baart
authors: Arnošt
authors: A
authors: Komárek
authors: Joost
authors: J
authors: van Rosmalen
authors: Emmanuel
authors: E
authors: Lesaffre
mesh_terms: D000328:Adult; D000367:Age Factors; 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; D012372:ROC Curve; D012044:Regression Analysis; D012621:Seasons; D012737:Sex Factors; D013997:Time Factors; D055815:Young Adult
chemical_list: D006454:Hemoglobins
references: Am J Clin Nutr. 1994 Jul;60(1):117-21
references: 8017324
references: Transfusion. 2007 Aug;47(8):1514-23
references: 17655597
references: Vox Sang. 2011 Feb;100(2):204-11
references: 20726956
references: Am J Clin Nutr. 2000 Aug;72(2 Suppl):594S-7S
references: 10919965
references: Clin Lab Haematol. 1997 Sep;19(3):177-81
references: 9352141
references: Transfus Apher Sci. 2005 Aug;33(1):31-5
references: 15951241
references: BMC Bioinformatics. 2011 Mar 17;12:77
references: 21414208
references: Eur J Clin Nutr. 1997 Nov;51 Suppl 3:S51-8
references: 9598769
references: Vox Sang. 2010 May;98(4):547-53
references: 19951306
references: Transfusion. 2012 Dec;52(12):2559-69
references: 22519683
references: Transfusion. 2007 May;47(5):895-900
references: 17465956
references: Eur J Epidemiol. 2006;21(7):493-9
references: 16858617
references: BMC Health Serv Res. 2005 May 11;5:36
references: 15885149
references: Radiology. 1983 Sep;148(3):839-43
references: 6878708
references: Transfusion. 1998 Feb;38(2):181-3
references: 9531951
references: Transfus Apher Sci. 2007 Jun;36(3):235-42
references: 17556020
references: Am J Clin Nutr. 1984 Mar;39(3):427-36
references: 6695842
references: Br J Haematol. 1993 Nov;85(3):603-7
references: 8136283
references: Am J Clin Nutr. 1989 Dec;50(6):1276-81
references: 2596419