title: Physiologic mechanisms can predict hematologic responses to iron supplements in growing children: a computer simulation model.
abstract: BACKGROUND
  Iron deficiency is the most common preventable nutrition problem in developing countries. Several randomized clinical trials (RCTs) have been conducted to determine the effectiveness of various iron dosing schemes in multiple settings.
  
  
  OBJECTIVE
  The objective was to determine whether enough is known about iron metabolism to predict hemoglobin and serum ferritin (SF) concentrations with a computer model and whether the model could be used as a substitute for new RCTs.
  
  
  METHODS
  Guided by the physiology of iron absorption and regulation, we used data from RCTs that tested iron Sprinkles to develop a computer model. Of 2 RCTs in Ghana, we used 1 to compute the amount of iron absorbed from a given dose in anemic and nonanemic children and the other to compute the resulting change in hemoglobin concentrations. We used this model to predict hemoglobin and SF concentrations in a new RCT in China and compared model-predicted values with actual values by using summary statistics (means and medians) and quantile-quantile plots.
  
  
  RESULTS
  The model-predicted hemoglobin means were within +/-2 g/L, and SF medians were within +/-3 microg/L of the corresponding means and medians of the actual values. On quantile-quantile plots, the predicted hemoglobin quantiles were within +/-5 g/L, and SF quantiles were within +/-10 microg/L of the corresponding quantiles of the actual values.
  
  
  CONCLUSIONS
  Our model of iron metabolism can accurately predict hemoglobin and SF concentrations after iron supplementation with Sprinkles in children; the model can thus obviate the need for repeating RCTs in multiple settings.
authors.affiliation: Department of Nutritional Sciences, University of Toronto, Toronto, Canada. doc.sharieff@utoronto.ca
authors.forename: Waseem
authors.initials: W
authors.lastname: Sharieff
authors.forename: Stanley
authors.initials: S
authors.lastname: Zlotkin
authors.forename: Melody
authors.initials: M
authors.lastname: Tondeur
authors.forename: Brian
authors.initials: B
authors.lastname: Feldman
authors.forename: George
authors.initials: G
authors.lastname: Tomlinson
mesh_terms: D018798:Anemia, Iron-Deficiency / Q000097:blood* / Q000188:drug therapy; D002648:Child; D002657:Child Development / Q000187:drug effects* / Q000502:physiology; D003198:Computer Simulation; D019587:Dietary Supplements; D005293:Ferritins / Q000097:blood*; D006454:Hemoglobins / Q000378:metabolism*; D006801:Humans; D007408:Intestinal Absorption; D019266:Iron, Dietary / Q000008:administration & dosage* / Q000493:pharmacokinetics; D008390:Markov Chains; D008954:Models, Biological; D009010:Monte Carlo Method; D011237:Predictive Value of Tests; D016032:Randomized Controlled Trials as Topic
chemical_list: D006454:Hemoglobins; D019266:Iron, Dietary; D005293:Ferritins