UCAN CAN-DU: Canada-Netherlands Personalized Medicine Network in Childhood Arthritis and Rheumatic Disease

Overview

Childhood arthritis is a chronic disabling disease. New medications called biologic therapies are now available to treat arthritis that target key biologic molecules that cause inflammation. Biologic therapies, while very effective in treating arthritis in children, may have serious side effects including infections and potentially cancers, and are very expensive and doctors don't know, which one to choose for which child. The investigators will develop tests that enable them to learn about the biology of each child's arthritis and be able to predict when and which biologic therapy to start and when to stop.

UCAN CAN-DU is a multicenter observational cohort study that will collect prospective data from children with arthritis. Biologic samples, clinical data and patient reported outcomes will be collected. In addition, the study will also include a health economics component which will include a number of complementary approaches for quantifying and comparing benefits and risks that promote evidence-based, patient centered health care. This will address both the personal and societal economic burden of disease and include qualitative methods to inform the measurement of preferences, economic and simulation modelling to assess the value of biomarker testing. The socioeconomic impact of biomarker based treatment will be evaluated. All clinical, biological and patient-derived data will be collected at an aggregation point housed and managed by High Performance Computing 4 Health (HPC4Health), a private hospital-only secure cloud-computing service within Compute Canada and physically located at SickKids/UHN. These databases and apps include biospecimen data and data collected through the eHealth platform. This will enable the study team to share and integrate data in near real-time into analytic models throughout the study course; hence providing a near real-time feedback from bench to bedside and vice versa. The analysis of the cohorts will help define and confirm the biologic pathways predictive of disease course, treatment response and disease remission. This knowledge will then be used to develop a comprehensive clinical predictive tool to guide effective and safe treatment of childhood arthritis.

Conditions