Usefulness of Different Biochemical Markers of the Insulin-Like Growth Factor (IGF) Family in Diagnosing Growth Hormone Excess and Deficiency in Adults<sup>1</sup>
Bibliographic record
Abstract
The diagnostic approach to acromegaly and GH deficiency frequently includes measurement of several components of the insulin-like growth factor (IGF) system. IGF-I levels are reported to be good predictors of active and cured acromegaly, but are commonly found within the normal age-adjusted range in adult GH-deficient (GHD) patients. Circulating concentrations of IGF-binding protein-3 (IGFBP-3), acid-labile subunit (ALS), and free IGF-I reflect the GH secretory status, but their diagnostic accuracy is still debated. In this study serum levels of total and free IGF-I, IGFBP-3, ALS, and IGFBP-3-IGF-I and IGFBP-3-ALS complexes were determined in patients previously diagnosed with active (n = 67) or inactive (n = 16) acromegaly and adult GHD (n = 34) and compared with results obtained in 58 healthy controls. In healthy subjects, IGF-I, IGFBP-3, ALS, and both IGFBP-3 complexes declined with age; a correlation was found between IGF-I and IGFBP-3 (r = 0.59; P < 0.001), ALS (r = 0.67; P < 0.001), and free IGF-I (r = 0.40; P < 0.05). Active acromegalic patients showed a significant increase in all parameters tested. IGF-I concentrations were above +2 SD in 100% of patients, whereas slightly lower sensitivities were shown for IGFBP-3 (85%), ALS (88%), and free IGF-I (94%). In this group, IGF-I exhibited a slightly higher correlation with IGFBP-3 (r = 0.83; P < 0.001) than with ALS levels (r = 0.78; P < 0.001). In cured acromegalic patients, we observed the normalization of all parameters but free IGF-I levels. Adult GHD patients showed a significant reduction of all hormones. Unlike active acromegalic patients, all parameters had only a modest sensitivity in GHD; suppression below -2 SD was observed in 41% of GHD patients for IGF-I, 47% for IGFBP-3, 32% for ALS, and 35% for free IGF-I measurements. Previous radiotherapy and GH peak response below 3 microg/L were associated with significantly lower IGF-I, IGFBP-3, and ALS levels. IGF-I levels were significantly correlated to ALS (r = 0.68; P < 0.001) and IGFBP-3 (r = 0.64; P < 0.001) as well as with free IGF-I (r = 0.67; P < 0.001) levels. By multiple regression analysis, the number of anterior pituitary hormones impaired was the most predictive indicator of IGF-I, IGFBP-3, and free IGF-I levels in GHD patients; conversely, the GH peak response better anticipated ALS concentrations. The pattern of IGFBP-3 complexes paralleled previous hormonal findings. In active acromegalic patients, IGFBP-3-IGF-I levels were 5.4-fold higher than in controls and were above +2 SD in 95% of patients, whereas IGFBP-3-ALS levels were elevated in 15% of cases. On the other hand, both IGFBP-3 complexes were able to predict GHD in only a minority of cases. Taken together, these data support the diagnostic role of IGF-I in acromegaly and suggest that free IGF-I and the IGFBP-3-IGF-I complex can assist diagnostic strategies in this condition. All markers are of limited predictive value in adult GHD, as hormonal values are commonly found within the normal limits. In these patients, low IGFBP-3 and IGF-I concentrations can add further clinical information on the residual GH activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".