AbstractChildren are considered a vulnerable group and as such are granted additional protection as research subjects. Research projects using children as research subjects are justifiable if the answer to the scientific question of the study cannot be obtained by enrolling adult subjects (cf. scientific necessity). Thus, there is an ethical obligation to explore innovative analytical strategies that seek balance between the feasibility of conducting a trial and maximizing the utilization of data on efficacy and safety. On this note, there is enthusiasm for implementing some less popular but efficient alternative designs for confirmatory pediatric trials. Within the pediatric extrapolation paradigm, examples of such designs, other than purely based on pharmacokinetic/pharmacodynamic data, are described in this article along with their advantages and disadvantages. This article will also discuss how to incorporate alternative data sources in the analysis of pediatric clinical trials. A discussion of existing approaches and a road-map to their utilization will be provided. Real case examples on the use of the approaches are provided. 相似文献
Introduction: Neuropsychological assessment of cognitive change over time is often conducted in clinical settings, but whether neuropsychological change scores are influenced by physical health has, as far as we know, not been examined previously.
Method: In a sample of 153 older Swedish adults (age range, 72–86 years), we evaluated the influence of common age-related diseases, terminal decline pathology, age, education, and gender, to provide (a) preliminary test-specific regression weights and 90% confidence intervals to assess significant change in performance after five years on tests of visual scanning, mental shifting, visual spatial ability, memory, reaction time, and selective attention, and (b) normative data for the Useful Field of View test (UFOV) from a single testing occasion.
Results: Multiple regression analyses showed that test–retest changes were affected by physical health for mental shifting, visual spatial ability, memory, and reaction time, by age for mental shifting and visual reaction time, by education for visual spatial ability, and by Age × Education for auditory reaction time. Gender did not affect any of the change scores. The overall average of variance explained was 2.5%: up to 8.1% for physical health, 4.4% for age, and 3.6% for education. The UFOV scores were mostly influenced by age, but also by physical health and education.
Conclusions: The findings indicate that considering the influence of health on normative change scores in old age in addition to demographic factors leads to more accurate predictions of whether true change has occurred. 相似文献