The validity of pediatric cancer diagnoses in a population-based general cancer registry in Ontario, Canada. Issue 1 (December 2016) - Gupta, Sumit; Pole, Jason
Abstract Background Data from population-based cancer registries are increasingly used to conduct research and guide policy. However, few validation studies of cancer registry data have been conducted, particularly among children. We therefore aimed to determine the validity of pediatric diagnostic data in the Ontario Cancer Registry (OCR). Methods All children diagnosed with any malignancy between 2000–2011 in Ontario, Canada were identified through the Pediatric Oncology Group of Ontario Networked Information System (POGONIS), a pediatric cancer registry actively maintained by trained data managers, and linked to the OCR. International Classification of Diseases for Oncology codes for each patient were taken from the OCR and converted to International Classification of Childhood Cancer (ICCC-3) diagnostic groups and subgroups using published algorithms. OCR-based ICCC-3 groupings were then validated by comparing them to gold standard diagnostic information from POGONIS. Results A total of 4448 patients met inclusion criteria; 4073 (91.6 %) were successfully linked to the OCR. Diagnostic accuracy was excellent for many childhood solid tumors. For example, the OCR correctly identified all cases of retinoblastoma [kappa = 1.00, 95th confidence interval (CI) 1.00–1.00] and nearly all cases of neuroblastoma (kappa = 0.97, 95th CI 0.96–0.99). Hematologic and central nervous system (CNS) cancers, the most common childhood malignancies, were however often misclassified with inferior kappas (acute lymphoblastic leukemia – 0.77, 95th CI 0.75–0.80; Burkitt lymphoma – 0.02, 95th CI 0.02–0.07). Conclusions Misclassification of common pediatric hematologic and CNS cancers was significant and may lead to inaccurate incidence and survival estimates using cancer registry data. Validation studies of pediatric data in other registries are necessary to identify practices and procedures leading to the highest quality information.