Evaluation of immunoassays for the measurement of insulin-like growth factor-I and procollagen type III peptide, indirect biomarkers of recombinant human growth hormone misuse in sport
Bibliographic record
Abstract
Insulin-like growth factor-I (IGF-I) and procollagen type III peptide (P-III-P) have been proposed as indirect biomarkers for the detection of the misuse of recombinant human growth hormone in sport. An extended intra- and inter-laboratory validation of commercially available immunoassays was carried out. For total IGF-I, two radioimmunoassay (RIA) kits (IGF-I/RIA1, Nichols Institute Diagnostics and IGF-I/RIA2, Mediagnost) and one enzyme-linked immunosorbent assay (ELISA) (R&D) were evaluated. For P-III-P, two RIA kits (P-III-P/RIA3, Cis-bioInternational and P-III-P/RIA4, Orion Diagnostica) were studied. The intra-laboratory precision and accuracy values for all IGF-I assays were better than 15%. The IGF-I/ELISA showed the lowest limit of quantification (LOQ) and its calibration curve covered the range of concentrations found in human serum samples. Higher agreement between laboratory results was obtained for IGF-I/ELISA and IGF-I/RIA1. Low inter-technique correlation was obtained for the three assays; the only comparable results were obtained between IGF-I/ELISA and IGF-I/RIA1. For P-III-P, intra-laboratory precision and accuracy values better than 15% were obtained for both assays in almost all cases. The calibration curve for P-III-P/RIA4 covered the range of concentrations of serum samples, while 30% of the values for P-III-P/RIA3 were below the calibration sample with the lowest concentration. Inter-laboratory correlation was also higher for P-III-P/RIA4. In summary, ELISA and RIA4 were the most suitable assays for measurement of IGF-I and P-III-P, respectively, in serum samples. However, the validation studies carried out show the need for harmonization of immunoassay parameters to improve the reproducibility and comparability of results between different laboratories and in different studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".