GH Stimulation testing is unnecessary in patients with hypothalamic-pituitary disease, preserved pituitary function, and IGF-I SDS ≥ 0.

Authors

Valentina Gasco, Daniela Cuboni, Michela Sibilla, Francesca Mocellini, Alice Martinotti, Davide Lucisano, Ezio Ghigo, Gianluca Aimaretti, Silvia Grottoli, Mauro Maccario

Published in

Pituitary. Volume 29. Issue 4. Jul 23, 2026. Epub Jul 23, 2026.

Abstract

In adults with hypothalamic-pituitary disease, the presence of at least three additional pituitary hormone deficiencies, with or without markedly reduced IGF-I levels, is considered diagnostic of growth hormone deficiency (GHD) without the need for stimulation testing. In all other cases, dynamic testing is required despite its well-recognized limitations. To date, no formal strategy has been proposed to exclude GHD without performing stimulation tests. This study aims to develop a probabilistic model to estimate the likelihood of GHD in adults with hypothalamic-pituitary disease but no additional pituitary hormone deficiencies, based on IGF-I standard deviation scores (SDS).
We combined literature-derived data on: (1) the probability of an impaired GH response to stimulation tests in patients with hypothalamic-pituitary disease and preserved anterior pituitary function; and (2) the probability that adults with isolated GHD present IGF-I SDS values ≥ 0, ≥ 0.5, or ≥ 1. A Bayesian approach was applied to estimate the post-test probability of GHD in patients meeting these criteria.
Across all models, the estimated probability of adult-onset GHD ranged from 6.5% to 19.8%, while the probability of childhood-onset GHD ranged from 2.9% to 9.1%, consistently remaining below 20%, regardless of the IGF-I SDS cut-off applied.
In adults with hypothalamic-pituitary disease but no additional hormonal deficiencies, IGF-I SDS values ≥ 0 identify a subgroup with a low, clinically acceptable probability of GHD, in whom stimulation testing may reasonably be avoided. This proof-of-concept model supports a simplified, probability-based diagnostic approach.

PMID:
42493668
Bibliographic data and abstract were imported from PubMed on 24 Jul 2026.

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