Models to predict changes in serum IGF1 and body composition in response to GH replacement therapy in GH-deficient adults

Abstract

Objective: Clinical response to GH therapy in GH-deficient (GHD) adults varies widely. Good predictors of treatment response are lacking. The aim of the study was to develop mathematical models to predict changes in serum IGF1 and body composition (BC) in response to GH therapy in GHD adults. Design and methods: One hundred and sixty-seven GHD patients (103 men, median age 50 years) were studied before and after 12 months of GH treatment. GH dose was tailored according to serum IGF1 concentrations. Good responders (GR) and poor responders (PR) to GH therapy were defined as patients with a response O60th and !40th percentile respectively, for changes in serum IGF1 levels (adjusted for GH cumulative dose) and in BC (lean body mass (LBM) and body fat determined using dual-energy X-ray absorptiometry). A logistic regression model was used to predict the probability of being a GR or PR. Results: In the IGF1 prediction model, men (odds ratio (OR) 5.62: 95% confidence interval 2.59-12.18) and patients with higher insulin levels (OR 1.06: 1.00-1.12) were more likely to be GR. The accuracy of the prediction model was 70%. In the BC model, men ) and GHD patients with lower LBM (OR 0.82: 0.73-0.92) and greater height (OR 1.23: 1.08-1.40) at baseline were more likely to be GR. The accuracy of the prediction model was 80%. Conclusion: Accurate mathematical models to predict GH responsiveness in GHD adults were developed using gender, body height, baseline LBM, and serum insulin levels as the major clinical predictors.

Efficacy and safety of growth hormone replacement therapy in Japanese adults with growth hormone deficiency: a post-marketing observational study

“…Previous studies in adult GHD have found an association between the response to GH and clinical and biochemical parameters, such as BMI, age, gender, serum GH-binding protein levels, GH dose, and the route of estrogen replacement in women [31,32]. Recently, Barbosa et al [33] developed mathematical models to predict GH responsiveness and found the clinical predictors of GH therapy were gender, serum insulin, BMI, and body fat at baseline. In the present study, we found that daily dose, IGF-I SD score at baseline and body fat were lower in those who were good responders for IGF-I.…”

SNPs within the GH-signaling pathway are associated with the early IGF1 response to GH replacement therapy in GHD adults

“…GH replacement therapy improves the metabolic abnormalities, but there is considerable variability in treatment response. Clinical variables, such as sex, age, BMI, GH dose, and the route of estrogen replacement in women have been linked to the response to GH replacement (3, 4, 5), but together these factors only explain a small part of the variability in GH treatment effect (6). Genetic factors, such as polymorphisms in genes within the GH signaling cascade, may also influence the responsiveness to GH.…”

Proposal of a clinical response score and predictors of clinical response to 2 years of GH replacement therapy in adult GH deficiency

“…This has been shown both in randomized placebo-controlled trials (1) and in large-scale observational studies (2,3,4,5,6,7,8,9,10,11,12).…”

“…In a previous KIMS analysis by FeldtRasmussen et al, sex, age and baseline IGF1 were predictors of IGF1 response and clinical changes to GHRT (11) In another study, sex was also the best predictor of favourable change in body fat and IGF1 response (9). In these studies, the association of different clinical baseline variables with IGF1 response and changes in clinical outcome variables such as weight, BMI, cholesterol and quality of life or body fat were analyzed.…”

“…The reason for this cut off was that the lowest two quintiles for a particular delta variable were associated with a worsening, whereas the upper three quintiles were associated with an improvement of that outcome (see Table 1). In clinical practice, a deterioration of the three response variables is observed over time without treatment (2,3,4,5,6,7,8,9,10,11,12). Therefore, we already considered an unchanged condition represented with a score of 7 as a response.…”