title: A third generation approach to detect erythropoietin abuse in athletes.
abstract: OBJECTIVE
  Information derived from blood analyses can assist in the detection and/or deterrence of blood doping in sport. We investigated whether comparing an athlete's hematologic values against his or her own historical baseline rather than population-derived thresholds enhanced the ability to detect blood doping.
  
  
  METHODS
  We developed an approach whereby an athlete's true baseline value could be estimated with just one prior blood test. We also estimated a universal value for within-subject variability for key hematologic parameters using the highest value obtained among four separate cohorts of male athletes including 80 elite rowers, 124 endurance-trained or team-sport subjects, 288 professional football players and 630 athletes competing at national or international level. The (individual) baseline and (universal) variability were then incorporated so as to define expected thresholds for subsequent blood tests. The sensitivity of our approach was obtained by analyzing data from 49 recreational athletes administered either recombinant human erythropoietin (n=37) or placebo (n=12).
  
  
  RESULTS
  We found that removing within-subject variability by comparing new results against an historical baseline heightened the capacity to detect blood doping. It was possible to delineate the longitudinal changes in either hemoglobin (Hb) or the OFF-hr model score (an algorithm using both Hb and percent reticulocytes) caused by recombinant human erythropoietin treatment from the natural biological fluctuations found in subjects treated with placebo.
  
  
  CONCLUSIONS
  Our objective data supported the intuitive belief that longitudinal monitoring of athletes' blood profiles will help detect blood doping. This information could be used to instigate target-testing of suspicious athletes, or even warrant the exclusion from competition of athletes with aberrant variations in key hematologic values.
authors.affiliation: Department of Mathematics and Statistics, University of Melbourne, Australia. k.sharpe@ms.unimelb.edu.au
authors.forename: Ken
authors.initials: K
authors.lastname: Sharpe
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Ashenden
authors.forename: Yorck O
authors.initials: YO
authors.lastname: Schumacher
mesh_terms: D015331:Cohort Studies; D004300:Doping in Sports; D004921:Erythropoietin / Q000097:blood*; D006801:Humans; D008297:Male; D015813:Substance Abuse Detection / Q000379:methods*; D019966:Substance-Related Disorders / Q000097:blood* / Q000175:diagnosis
chemical_list: D004921:Erythropoietin