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Fluctuations in plasma volume (PV) present potential confounders within the concentration‐based markers of the haematological athlete biological passport (ABP). Here, a multi‐parametric approach involving a simple blood test is applied to the current ABP adaptive model in an attempt to remove the influence of PV expansion, induced by a cycling stage race. Blood samples were obtained from 29 professional cyclists (14 male, 15 female) before, during and after 4–5 consecutive days of racing. Whole blood was analysed in accordance with the World Anti‐Doping Agency ABP guidelines for haemoglobin ([Hb]) concentration and platelets. Serum and plasma were analysed for transferrin, albumin, calcium, creatinine, total protein and low‐density lipoprotein. PV variation (Z‐scores) was estimated using a multi‐parametric model (consisting of the biomarkers mentioned earlier) and compared against calculated variations in PV (measured via CO‐rebreathing). Significant reductions in [Hb] and the OFF‐score were observed in female cyclists after 3 and 4 days of racing, with accompanying increases in PV, which returned to baseline values 4 days post competition. Similarly, a significant increase in PV was observed in male cyclists after 3 and 5 days of racing. When individual estimations of PV variance were applied to the adaptive model, the upper and lower reference predictions for [Hb] and the OFF‐score were refined such that all outliers consistent with racing‐induced PV changes were removed. The PV model appears capable of reducing the influence of PV on concentration‐dependent markers during competition. This is an important step towards the inclusion of the PV correction in the ABP haematological module. [ABSTRACT FROM AUTHOR]

Abstract: Altitude is a confounding factor within the Athlete Biological Passport (ABP) due, in part, to the plasma volume (PV) response to hypoxia. Here, a newly developed PV blood test is applied to assess the possible efficacy of reducing the influence of PV on the volumetric ABP markers; haemoglobin concentration ([Hb]) and the OFF‐score. Endurance athletes (n=34) completed a 21‐night simulated live‐high train‐low (LHTL) protocol (14 h.d‐1 at 3000 m). Bloods were collected twice pre‐altitude; at days 3, 8, and 15 at altitude; and 1, 7, 21, and 42 days post‐altitude. A full blood count was performed on the whole blood sample. Serum was analysed for transferrin, albumin, calcium, creatinine, total protein, and low‐density lipoprotein. The PV blood test (consisting of the serum markers, [Hb] and platelets) was applied to the ABP adaptive model and new reference predictions were calculated for [Hb] and the OFF‐score, thereby reducing the PV variance component. The PV correction refined the ABP reference predictions. The number of atypical passport findings (ATPFs) for [Hb] was reduced from 7 of 5 subjects to 6 of 3 subjects. The OFF‐score ATPFs increased with the PV correction (from 9 to 13, 99% specificity); most likely the result of more specific reference limit predictions combined with the altitude‐induced increase in red cell production. Importantly, all abnormal biomarker values were identified by a low confidence value. Although the multifaceted, individual physiological response to altitude confounded some results, the PV model appears capable of reducing the impact of PV fluctuations on [Hb]. [ABSTRACT FROM AUTHOR]

The haematological module of the Athlete's Biological Passport (ABP) has significantly impacted the prevalence of blood manipulations in elite sports. However, the ABP relies on a number of concentration?] based markers of erythropoiesis, such as haemoglobin concentration ([Hb]), which are influenced by shifts in plasma volume (PV). Fluctuations in PV contribute to the majority of biological variance associated with volumetric ABP markers. Our laboratory recently identified a panel of common chemistry markers (from a simple blood test) capable of describing ca 67% of PV variance, presenting an applicable method to account for volume shifts within anti?]doping practices. Here, this novel PV marker was included into the ABP adaptive model. Over a six-month period (one test per month), 33 healthy, active males provided blood samples and performed the COrebreathing method to record PV (control). In the final month participants performed a single maximal exercise effort to promote a PV shift (mean PV decrease -17%, 95% CI -9.75 to -18.13%). Applying the ABP adaptive model, individualized reference limits for [Hb] and the OFF-score were created, with and without the PV correction. With the PV correction, an average of 66% of [Hb] within-subject variance is explained, narrowing the predicted reference limits, and reducing the number of atypical ABP findings post-exercise. Despite an increase in sensitivity there was no observed loss of specificity with the addition of the PV correction. The novel PV marker presented here has the potential to improve the ABP's rate of correct doping detection by removing the confounding effects of PV variance. [ABSTRACT FROM AUTHOR]

The Athlete Biological Passport (ABP) estimates individualized reference ranges for key blood markers, such as haemoglobin concentration ([Hb]), using predetermined population mean, between- and within-subject variances. Here, we aim to reassess previously published estimates for within-subject [Hb] variance and determine whether sex-, analyzer-, sport-, or season-specific values are required. Our reference population contains 7723 male (mean ± SD, 22.3 ± 4.6 years of age) and 6164 female (21.6 ± 4.3) athlete observations from 49 sports. [Hb] was calculated using one of three cytometers; Bayer-H3 (1997-1999, n = 4554), ADVIA-120 (1999-2010, n = 8636) and Sysmex XT-2000i (2010-2012, n = 697). The final model was a linear mixed model for [ Hb] with analyzer (H3, ADVIA, Sysmex), sex (male, female), sport (power-endurance, endurance, skill, team, disabled and non-athletes), season (summer, winter), and the interaction between sex and sport as fixed effects and athlete as a random effect. The model included an exponential correlation structure to allow for within-subject autocorrelation, and allowed different within-subject variances for each sport. Within-subject [Hb] variance (g2/L2) was significantly less for power endurance (35.09, 95% CI 33.50 to 36.76), disabled (25.82, 95% CI 21.71 to 35.28) and non-athletes (34.30, 95% CI 28.53 to 35.87) than for endurance (40.35, 95% CI 39.62 to 47.22) and team sports (38.70, 95% CI 37.68 to 39.76) athletes. No new evidence was found to justify adjusting the current within-subject [Hb] variance estimate. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]