Background: Childhood obesity can result in adverse health outcomes. The objectives of this study were to describe the prevalence of obesity and determine the association between obesity at cancer diagnosis and event-free survival (EFS) and overall survival (OS) in children diagnosed with cancer in Canada.
Methods: The authors conducted a retrospective cohort study using the Cancer in Young People in Canada database, including all children with newly diagnosed cancer aged 2-18 years across Canada from 2001 to 2020.
Motor behaviour using upper-extremity prostheses of different levels is greatly variable, leading to challenges interpreting ideal rehabilitation strategies. Elucidating the underlying neural control mechanisms driving variability benefits our understanding of adaptation after limb loss. In this follow-up study, non-amputated participants completed simple and complex reach-to-grasp motor tasks using a body-powered transradial or partial-hand prosthesis simulator.
View Article and Find Full Text PDFDuring drug development, evidence can emerge to suggest a treatment is more effective in a specific patient subgroup. Whilst early trials may be conducted in biomarker-mixed populations, later trials are more likely to enroll biomarker-positive patients alone, thus leading to trials of the same treatment investigated in different populations. When conducting a meta-analysis, a conservative approach would be to combine only trials conducted in the biomarker-positive subgroup.
View Article and Find Full Text PDFSupporting schooling for current and past pediatric oncology patients is vital to their quality of life and psychosocial recovery. However, no study has examined the perspectives toward in-person schooling among pediatric oncology families during the COVID-19 pandemic. In this online survey study, we determined the rate of and attitudes toward in-person school attendance among current and past pediatric oncology patients living in Ontario, Canada during the 2020-2021 school year.
View Article and Find Full Text PDFObjectives: We aimed to develop a network meta-analytic model for the evaluation of treatment effectiveness within predictive biomarker subgroups, by combining evidence from individual participant data (IPD) from digital sources (in the absence of randomized controlled trials) and aggregate data (AD).
Study Design And Setting: A Bayesian framework was developed for modeling time-to-event data to evaluate predictive biomarkers. IPD were sourced from electronic health records, using a target trial emulation approach, or digitized Kaplan-Meier curves.