Statistical methodology for age-adjustment of the GH-2000 score detecting growth hormone misuse
Statistical methodology for age-adjustment of the GH-2000 score detecting growth hormone misuse
Background: The GH-2000 score has been developed as a powerful and unique technique for the detection of growth hormone misuse by sportsmen and women. The score depends upon the measurement of two growth hormone (GH) sensitive markers, insulin-like growth factor-I (IGF-I) and the amino-terminal pro-peptide of type III collagen (P-III-NP). With the collection and establishment of an increasingly large database it has become apparent that the score shows a positive age effect in the male athlete population, which could potentially place older male athletes at a disadvantage.
Methods: We have used results from residual analysis of the general linear model to show that the residual of the GH-2000 score when regressed on the mean-age centred age is an appropriate way to proceed to correct this bias. As six GH-2000 scores are possible depending on the assays used for determining IGF-I and P-III-NP, methodology had to be explored for including six different age effects into a unique residual. Meta-analytic techniques have been utilized to find a summary age effect.
Results: The age-adjusted GH-2000 score, a form of residual, has similar mean and variance as the original GH-2000 score and, hence, the developed decision limits show negligible change when compared to the decision limits based on the original score. We also show that any further scale-transformation will not change the adjusted score. Hence the suggested adjustment is optimal for the given data. The summary age effect is homogeneous across the six scores, and so the generic adjustment of the GH-2000 score formula is justified.
Conclusions: A final revised GH-2000 score formula is provided which is independent of the age of the athlete under consideration.
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Böhning, Walailuck
c0e89cb8-3d21-433c-8ca1-c1ee7c5bdfa6
Guha, Nishan
38212040-a65e-4874-a60a-21f0ae3bdf09
Cowan, David A.
22bdafa8-cee8-481a-97d5-2687fcf325ca
Sönksen, Peter H.
b3cf05ef-65c2-4e9b-8d95-b7c3aaf532cd
Holt, Richard I.G.
d54202e1-fcf6-4a17-a320-9f32d7024393
28 October 2016
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Böhning, Walailuck
c0e89cb8-3d21-433c-8ca1-c1ee7c5bdfa6
Guha, Nishan
38212040-a65e-4874-a60a-21f0ae3bdf09
Cowan, David A.
22bdafa8-cee8-481a-97d5-2687fcf325ca
Sönksen, Peter H.
b3cf05ef-65c2-4e9b-8d95-b7c3aaf532cd
Holt, Richard I.G.
d54202e1-fcf6-4a17-a320-9f32d7024393
Böhning, Dankmar, Böhning, Walailuck, Guha, Nishan, Cowan, David A., Sönksen, Peter H. and Holt, Richard I.G.
(2016)
Statistical methodology for age-adjustment of the GH-2000 score detecting growth hormone misuse.
BMC Medical Research Methodology, 16 (147).
(doi:10.1186/s12874-016-0246-8).
Abstract
Background: The GH-2000 score has been developed as a powerful and unique technique for the detection of growth hormone misuse by sportsmen and women. The score depends upon the measurement of two growth hormone (GH) sensitive markers, insulin-like growth factor-I (IGF-I) and the amino-terminal pro-peptide of type III collagen (P-III-NP). With the collection and establishment of an increasingly large database it has become apparent that the score shows a positive age effect in the male athlete population, which could potentially place older male athletes at a disadvantage.
Methods: We have used results from residual analysis of the general linear model to show that the residual of the GH-2000 score when regressed on the mean-age centred age is an appropriate way to proceed to correct this bias. As six GH-2000 scores are possible depending on the assays used for determining IGF-I and P-III-NP, methodology had to be explored for including six different age effects into a unique residual. Meta-analytic techniques have been utilized to find a summary age effect.
Results: The age-adjusted GH-2000 score, a form of residual, has similar mean and variance as the original GH-2000 score and, hence, the developed decision limits show negligible change when compared to the decision limits based on the original score. We also show that any further scale-transformation will not change the adjusted score. Hence the suggested adjustment is optimal for the given data. The summary age effect is homogeneous across the six scores, and so the generic adjustment of the GH-2000 score formula is justified.
Conclusions: A final revised GH-2000 score formula is provided which is independent of the age of the athlete under consideration.
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Accepted/In Press date: 13 October 2016
e-pub ahead of print date: 28 October 2016
Published date: 28 October 2016
Organisations:
Statistics, Human Nutrition & Metabolism, Human Development & Health, Medicine, Southampton Marine & Maritime Institute
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Local EPrints ID: 410334
URI: http://eprints.soton.ac.uk/id/eprint/410334
ISSN: 1471-2288
PURE UUID: cb473396-16a9-469b-81fb-035ea5a3ccd7
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Date deposited: 07 Jun 2017 16:30
Last modified: 16 Mar 2024 04:07
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Author:
Walailuck Böhning
Author:
Nishan Guha
Author:
David A. Cowan
Author:
Peter H. Sönksen
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