CONTEXT: Somapacitan is a long-acting growth hormone (GH) in development for once-weekly treatment of GH deficiency (GHD). Optimal monitoring of insulin-like growth factor-I (IGF-I) levels must account for weekly IGF-I fluctuations following somapacitan administration. OBJECTIVE: To develop and assess the reliability of linear models for predicting mean and peak IGF-I levels from samples taken on different days after dosing. DESIGN: A pharmacokinetic/pharmacodynamic model was used to simulate IGF-I data in adults and children following weekly somapacitan treatment of GHD. SETTING AND PATIENTS: 39 200 IGF-I profiles were simulated with reference to data from 26 adults and 23 children with GHD. INTERVENTION(S): The simulated dose range was 0.02 to 0.12 mg/kg for adults and 0.02 to 0.16 mg/kg for children. Simulated data with >4 average standard deviation score were excluded. MAIN OUTCOME MEASURE(S): Linear models for predicting mean and peak IGF-I levels based on IGF-I samples from different days after somapacitan dose. RESULTS: Robust linear relationships were found between IGF-I sampled on any day after somapacitan dose and the weekly mean (R2 > 0.94) and peak (R2 > 0.84). Prediction uncertainties were generally low when predicting mean from samples taken on any day (residual standard deviation [RSD] ≤ 0.36) and peak from samples taken on day 1 to 4 (RSD ≤ 0.34). IGF-I monitoring on day 4 and day 2 after dose provided the most accurate estimate of IGF-I mean (RSD < 0.2) and peak (RSD < 0.1), respectively. CONCLUSIONS: Linear models provided a simple and reliable tool to aid optimal monitoring of IGF-I by predicting mean and peak IGF-I levels based on an IGF-I sample following dosing of somapacitan. A short visual summary of our work is available (1).
CONTEXT: Somapacitan is a long-acting growth hormone (GH) in development for once-weekly treatment of GH deficiency (GHD). Optimal monitoring of insulin-like growth factor-I (IGF-I) levels must account for weekly IGF-I fluctuations following somapacitan administration. OBJECTIVE: To develop and assess the reliability of linear models for predicting mean and peak IGF-I levels from samples taken on different days after dosing. DESIGN: A pharmacokinetic/pharmacodynamic model was used to simulate IGF-I data in adults and children following weekly somapacitan treatment of GHD. SETTING AND PATIENTS: 39 200 IGF-I profiles were simulated with reference to data from 26 adults and 23 children with GHD. INTERVENTION(S): The simulated dose range was 0.02 to 0.12 mg/kg for adults and 0.02 to 0.16 mg/kg for children. Simulated data with >4 average standard deviation score were excluded. MAIN OUTCOME MEASURE(S): Linear models for predicting mean and peak IGF-I levels based on IGF-I samples from different days after somapacitan dose. RESULTS: Robust linear relationships were found between IGF-I sampled on any day after somapacitan dose and the weekly mean (R2 > 0.94) and peak (R2 > 0.84). Prediction uncertainties were generally low when predicting mean from samples taken on any day (residual standard deviation [RSD] ≤ 0.36) and peak from samples taken on day 1 to 4 (RSD ≤ 0.34). IGF-I monitoring on day 4 and day 2 after dose provided the most accurate estimate of IGF-I mean (RSD < 0.2) and peak (RSD < 0.1), respectively. CONCLUSIONS: Linear models provided a simple and reliable tool to aid optimal monitoring of IGF-I by predicting mean and peak IGF-I levels based on an IGF-I sample following dosing of somapacitan. A short visual summary of our work is available (1).
Authors: Dianne Kremidas; Tami Wisniewski; Victoria M Divino; Kaysen Bala; Maryann Olsen; John Germak; Mark Aagren; Natalia Holot; Won Chan Lee Journal: J Pediatr Nurs Date: 2012-01-30 Impact factor: 2.145
Authors: Pinchas Cohen; Alan D Rogol; Campbell P Howard; George M Bright; Anne-Marie Kappelgaard; Ron G Rosenfeld Journal: J Clin Endocrinol Metab Date: 2007-03-13 Impact factor: 5.958
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Authors: Andrew R Hoffman; Joyce E Kuntze; Joyce Baptista; Howard B A Baum; Gerhard P Baumann; Beverly M K Biller; Richard V Clark; David Cook; Silvio E Inzucchi; David Kleinberg; Anne Klibanski; Lawrence S Phillips; E Chester Ridgway; Richard J Robbins; Janet Schlechte; Meeta Sharma; Michael O Thorner; Mary Lee Vance Journal: J Clin Endocrinol Metab Date: 2004-05 Impact factor: 5.958
Authors: D B Allen; P Backeljauw; M Bidlingmaier; B M K Biller; M Boguszewski; P Burman; G Butler; K Chihara; J Christiansen; S Cianfarani; P Clayton; D Clemmons; P Cohen; F Darendeliler; C Deal; D Dunger; E M Erfurth; J S Fuqua; A Grimberg; M Haymond; C Higham; K Ho; A R Hoffman; A Hokken-Koelega; G Johannsson; A Juul; J Kopchick; P Lee; M Pollak; S Radovick; L Robison; R Rosenfeld; R J Ross; L Savendahl; P Saenger; H T Sorensen; K Stochholm; C Strasburger; A Swerdlow; M Thorner Journal: Eur J Endocrinol Date: 2015-11-12 Impact factor: 6.664