Patient-Reported Outcomes Over 24 Months in Pediatric CKD: Findings From the MyKidneyHealth Cohort Study.

2023

03/2023

1523-6838

RATIONALE AND OBJECTIVE: The lived experience of children with chronic kidney disease (CKD) is poorly characterized. We examined the associations between patient-reported outcomes (PROs) measuring children's fatigue, sleep health, psychological distress, family relationships, and global health with clinical outcomes over time in children with CKD and investigated how PROs of children with CKD compare with those of other children.

STUDY DESIGN: Prospective cohort study.

SETTING AND PARTICIPANTS: 212 children 8-21 years-old with CKD and their parents recruited from 16 nephrology programs across North America.

PREDICTORS: CKD stage, disease etiology, sociodemographic and clinical variables.

OUTCOMES: PROs over 2 years.

ANALYTICAL APPROACH: We compared PROs in the CKD sample with a nationally representative general pediatric population. Change of PROs over time and association of sociodemographic and clinical variables with PROs were assessed using multivariable regression models.

RESULTS: 84% parents and 77% children completed PROs at all time points. Baseline PRO scores for children with CKD revealed higher burden of fatigue, sleep-related impairment, psychological distress, impaired global health, and poorer family relationships compared with the general pediatric population, with median score differences ≥ one standard deviation for fatigue and global health. Baseline PRO scores did not differ by CKD stage or glomerular vs. non-glomerular etiology. Over two years, PROs were stable with < 1-point annual change on average on each measure and intraclass correlation coefficients ranging 0.53 to 0.79, indicating high stability. Hospitalization and parent-reported sleep problems were associated with worse fatigue, psychological health and global health scores (all p<0.04).

LIMITATIONS: Unable to assess responsiveness to change with dialysis or transplant.

CONCLUSIONS: Children with CKD experience high, yet stable burden of impairment across numerous PRO measures, especially fatigue and global health, independent of disease severity. These findings underscore the importance of assessing PRO, including fatigue and sleep measures, in this vulnerable population.

10.1053/j.ajkd.2022.12.014

Am J Kidney Dis

36889426

Use of normalized prediction distribution errors for assessing population physiologically-based pharmacokinetic model adequacy.

2020

2020 Apr 22

1573-8744

<p>Currently employed methods for qualifying population physiologically-based pharmacokinetic (Pop-PBPK) model predictions of continuous outcomes (e.g., concentration-time data) fail to account for within-subject correlations and the presence of residual error. In this study, we propose a new method for evaluating Pop-PBPK model predictions that account for such features. The approach focuses on deriving Pop-PBPK-specific normalized prediction distribution errors (NPDE), a metric that is commonly used for population pharmacokinetic model validation. We describe specific methodological steps for computing NPDE for Pop-PBPK models and define three measures for evaluating model performance: mean of NPDE, goodness-of-fit plots, and the magnitude of residual error. Utility of the proposed evaluation approach was demonstrated using two simulation-based study designs (positive and negative control studies) as well as pharmacokinetic data from a real-world clinical trial. For the positive-control simulation study, where observations and model simulations were generated under the same Pop-PBPK model, the NPDE-based approach denoted a congruency between model predictions and observed data (mean of NPDE =  - 0.01). In contrast, for the negative-control simulation study, where model simulations and observed data were generated under different Pop-PBPK models, the NPDE-based method asserted that model simulations and observed data were incongruent (mean of NPDE =  - 0.29). When employed to evaluate a previously developed clindamycin PBPK model against prospectively collected plasma concentration data from 29 children, the NPDE-based method qualified the model predictions as successful (mean of NPDE = 0). However, when pediatric subpopulations (e.g., infants) were evaluated, the approach revealed potential biases that should be explored.</p>

10.1007/s10928-020-09684-2

J Pharmacokinet Pharmacodyn

32323049