Combined statistical decision limits based on two GH-2000 scores for the detection of growth hormone misuse

Abstract

The GH-2000 biomarker method, based on the measurements of insulin-like growth factor-I (IGF-I) and the amino-terminal pro-peptide of type III collagen (P-III-NP), has been developed as a powerful technique for the detection of growth hormone (GH) misuse by athletes. IGF-I and P-III-NP are combined in gender specic formulas to create the GH-2000 score, which is used to determine whether GH has been administered. To comply with World Anti-Doping Agency regulations, each analyte must be measured by two methods. IGF-I and P-III-NP can be measured by a number of approved methods, each leading to its own GH-2000 score. Single decision limits for each GH-2000 score have been originally developed by Bassett and co-workers (Erotokritou-Mulligan et al. (2012) and further developed in Holt et al. (2015) and B�ohning et al. (2019).
These have been incorporated into the guidelines of the World Anti-Doping Agency. Erotokritou-Mulligan et al. (2012) and Holt et al. (2015) constructed a joint decision limit based on the sample correlation between the two GH-2000 scores generated from an available sample in order to increase the sensitivity of the biomarker method. This paper takes this idea further into a fully developed statistical approach. It constructs combined decision limits when two GH-2000 scores from different assay combinations are used to decide whether an athlete has been misusing GH. The combined decision limits are directly related to tolerance regions and constructed using a Bayesian approach. It is also shown to have highly satisfactory frequentist properties. The new approach meets the required false-positive rate with a pre-specied level of certainty.

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Identifiers

ORCID for Wei Liu: orcid.org/0000-0002-4719-0345

ORCID for Dankmar Bohning: orcid.org/0000-0003-0638-7106

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