Procollagen type III amino‐terminal propeptide and insulin‐like growth factor I as biomarkers of growth hormone administration
Bibliographic record
Abstract
The acceptance in 2012 by the World Anti-Doping Agency (WADA) of the biomarker test for human growth hormone (hGH) based on procollagen type III amino-terminal propeptide (P-III-NP) and insulin-like growth factor I (IGF-I) was perhaps the first time that such a method has been used for forensic purposes. Developing a biomarker test to anti-doping standards, where the strict liability principle applies, is discussed. An alternative WADA-accepted approach is based on the measurement of different hGH isoforms, a method that suffers from the very short half-life of hGH limiting the detection period. Modification or withdrawal of the immunoassays, on which the biomarker measurements largely depend, has necessitated revalidation of the assays, remeasurement of samples and adjustment of the decision limits above which an athlete will be assumed to have administered hGH. When a liquid chromatography coupled mass spectrometry (LC-MS) method became a reality for the measurement of IGF-I, more consistency of results was assured. Measurement of P-III-NP is still dependent on immunoassays although work is underway to develop an LC-MS method. The promised long-term detection time for the biomarker assay does not appear to have been realised in practice, and this is perhaps partly the result of decision limits being set too high. Nevertheless, more robust assays are needed before a further adjustment of the decision limit is warranted. In the meantime, WADA is considering using P-III-NP and IGF-I as components of a biomarker passport system recording data from an individual athlete, rather than the population. Using this approach, smaller perturbations in the growth hormone (GH) score would mandate an investigation and possible action for hGH administration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".