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Models predicting the growth response to growth hormone treatment in short children independent of GH status, birth size and gestational age.
Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
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2007 (English)In: BMC medical informatics and decision making, ISSN 1472-6947, Vol. 7, 40- p.Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Mathematical models can be used to predict individual growth responses to growth hormone (GH) therapy. The aim of this study was to construct and validate high-precision models to predict the growth response to GH treatment of short children, independent of their GH status, birth size and gestational age. As the GH doses are included, these models can be used to individualize treatment. METHODS: Growth data from 415 short prepubertal children were used to construct models for predicting the growth response during the first years of GH therapy. The performance of the models was validated with data from a separate cohort of 112 children using the same inclusion criteria. RESULTS: Using only auxological data, the model had a standard error of the residuals (SDres), of 0.23 SDS. The model was improved when endocrine data (GHmax profile, IGF-I and leptin) collected before starting GH treatment were included. Inclusion of these data resulted in a decrease of the SDres to 0.15 SDS (corresponding to 1.1 cm in a 3-year-old child and 1.6 cm in a 7-year old). Validation of these models with a separate cohort, showed similar SDres for both types of models. Preterm children were not included in the Model group, but predictions for this group were within the expected range. CONCLUSION: These prediction models can with high accuracy be used to identify short children who will benefit from GH treatment. They are clinically useful as they are constructed using data from short children with a broad range of GH secretory status, birth size and gestational age.

Place, publisher, year, edition, pages
2007. Vol. 7, 40- p.
URN: urn:nbn:se:umu:diva-21707DOI: 10.1186/1472-6947-7-40PubMedID: 18076760OAI: diva2:211620
Available from: 2009-04-16 Created: 2009-04-16 Last updated: 2010-10-13

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