Document Detail

A mathematical model in the analysis of the response to growth hormone treatment in pediatric patients with diagnosis of growth hormone deficiency.
MedLine Citation:
PMID:  22490990     Owner:  NLM     Status:  In-Data-Review    
In the literature, few studies analyze the effect of GH therapy on height, preferring a more indirect approach, where factors influencing the total pubertal and pre-pubertal growth in GH-deficient patients are evaluated and subsequently used to estimate the overall effect at the end of the therapy; unfortunately, this approach does not quantify the real growth gain in treated patients. Using a non-parametric Empirical Bayes approach, our study analyzes the growth response to GH treatment in a homogeneous cohort of 317 patients with pituitary GH deficiency who were enrolled during their pre-pubertal stage in the GH Piedmont Registry (Italy), between January 2000-October 2008, and have at least 2 yr of follow-up. To estimate the growth curve for males and females, a non-parametric regression model was fitted, applying Empirical Bayes techniques. A validation of the model was also performed. Improvement was evident in both genders, since both males and females mean growth curve, which started below the 3rd percentile at the beginning of the therapy, reached the 10th percentile of the Tanner curve at the end of observation (17 yr old for males and 14 yr old for females); the estimation procedure achieved a good precision. The methodological approach allows for fitting a model able to evaluate longitudinally the response to GH treatment, by means of estimating the overall growth curve, even in presence of sparse information about children heights.
G Migliaretti; P Berchialla; A Borraccino; D Gregori; F Cavallo;
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of endocrinological investigation     Volume:  35     ISSN:  1720-8386     ISO Abbreviation:  J. Endocrinol. Invest.     Publication Date:  2012 Feb 
Date Detail:
Created Date:  2012-04-11     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7806594     Medline TA:  J Endocrinol Invest     Country:  Italy    
Other Details:
Languages:  eng     Pagination:  209-14     Citation Subset:  IM    
Department of Public Health and Microbiology, University of Turin, V. Santena 5bis, Turin 10100, Italy.
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MeSH Terms
A Angeli / ; G Aimaretti / ; J Bellone / ; L Benso / ; G Bona / ; F Camanni / ; C De Sanctis / ; P Matarazzo / ; A Ravaglia / ; S Vannelli /

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