Caucasian paediatric kidney transplant recipients
Conditions
Brief summary
Full AUCs will be described by median, minimum and maximum, geometric mean, arithmetic mean, standard deviation and coefficient of variation and analysed using an ANOVA model on the log transformed AUC values comparing Envarsus® and Prograf® with sequence, subject within sequence and period as further fixed factors. The resulting 90% confidence interval must lie within the acceptance boundaries of 0.8 and 1.25.
Detailed description
The secondary pharmacokinetic and pharmacodynamic endpoints will be analysed analogous to the primary endpoint or assessed using descriptive statistics (such as absolute and relative frequencies, median and interquartile range, geometric mean, arithmetic mean and standard deviation, minimum and maximum and coefficients of variation) to compare both phases. The suitability of LSS for 24h-AUC calculation will be judged using Pearson’s correlation coefficients.
Interventions
Sponsors
Eligibility
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Full AUCs will be described by median, minimum and maximum, geometric mean, arithmetic mean, standard deviation and coefficient of variation and analysed using an ANOVA model on the log transformed AUC values comparing Envarsus® and Prograf® with sequence, subject within sequence and period as further fixed factors. The resulting 90% confidence interval must lie within the acceptance boundaries of 0.8 and 1.25. | — |
Secondary
| Measure | Time frame |
|---|---|
| The secondary pharmacokinetic and pharmacodynamic endpoints will be analysed analogous to the primary endpoint or assessed using descriptive statistics (such as absolute and relative frequencies, median and interquartile range, geometric mean, arithmetic mean and standard deviation, minimum and maximum and coefficients of variation) to compare both phases. The suitability of LSS for 24h-AUC calculation will be judged using Pearson’s correlation coefficients. | — |
Countries
Germany