Practice guidelines cannot recommend establishing a diagnosis of growth hormone deficiency (GHD) without performing growth hormone stimulation tests (GHST) in children with risk factors, due to the lack of sufficient evidence.
Our goal was to generate an evidence-based prediction rule to diagnose GHD in children with growth failure and clinically identifiable risk factors.
We studied a cohort of children with growth failure to build the prediction model, and a second, independent cohort to validate the prediction rule. To this end, we assessed the existence of: pituitary dysgenesis, midline abnormalities, (supra)sellar tumor/surgery, CNS infection, traumatic brain injury, cranial radiotherapy, chemotherapy, genetic GHD, pituitary hormone deficiencies, and neonatal hypoglycemia, cholestasis, or hypogenitalism. Selection of variables for model building was performed using artificial intelligence protocols. Specificity of the prediction rule was the main outcome measure in the validation set.
In the first cohort (n=770), the resulting prediction rule stated that a patient would have GHD if (s)he had: pituitary dysgenesis, or two or more anterior pituitary deficiencies, or one anterior pituitary deficiency plus: neonatal hypoglycemia or hypogenitalism, or diabetes insipidus, or midline abnormalities, or (supra)sellar tumor/surgery, or cranial radiotherapy ≥18 Gy. In the validation cohort (n=161), the specificity of the prediction rule was 99.2% (95% CI: 95.6–100%).
This clinical rule predicts the existence of GHD with high specificity in children with growth disorders and clinically identifiable risk factors, thus providing compelling evidence to recommend that GHD can be safely diagnosed without recurring to GHST in neonates and children with growth failure and specific comorbidities.