Canadian data sources for paediatric oncology
POGONIS (Pediatric Oncology Group of Ontario Networked Information System) is a population-based registry containing diagnostic and treatment-related information for all children and adolescents diagnosed with cancer and/or treated for cancer in a specialized childhood cancer program in Ontario.
The Initiative to Maximize Progress in Adolescent and Young Adult Cancer Therapy (IMPACT) cohort is housed at ICES and contains detailed diagnostic and treatment data for AYAs aged 15–29 in Ontario.
The Cancer in Young People in Canada (CYP-C) surveillance system collects pan-Canadian data on children and youth with cancer to inform research and planning for cancer control efforts. The CYP-C data tool contains information on incidence, survival, prevalence, mortality and relapse risk.
ICES leads cutting-edge studies that evaluate healthcare delivery and outcomes. It encompasses much of the publicly funded administrative health services records for the Ontario population eligible for universal health coverage since 1986. This allows for the linkage of Ontario-based cancer registry databases (e.g., POGONIS, IMPACT) to various sources of anonymized health records (e.g., hospitalizations).
The Statistics Canada Social Data Linkage Environment (SDLE) promotes the innovative use of existing administrative and survey data in Canada to address important research questions and inform socio-economic policy through record linkage. Using the SDLE, anonymized cancer registry data can be linked to data sources related to income, employment, and education.
Prediction and simulation models
POSIM is a web-based, interactive platform that hosts decision analytic models and disease models developed (in R) by scientists and paediatric oncologists at The Hospital for Sick Children (SickKids) in Toronto, Canada.
Some research from the North American Childhood Cancer Survivor Study (CCSS) has resulted in the development of future risk calculators to better understand potential outcomes for survivors.
Methodological resources
The Decision Analysis in R for Technologies in Health (DARTH) group is a multi-institutional, multi-university collaborative effort comprised of researchers who have a passion for transparent and open-source solutions to decision analysis in health. The aim of this collaboration is to expand knowledge in decision analysis using R and develop educational material that empowers people to construct R-based decision models.