BACKGROUND AND OBJECTIVES: The Ontario Cancer Registry (OCR) is a population-based tumor registry created to provide data for epidemiologic research and for cancer surveillance. Recently it has been used for health services research. The objective of this project was to assess the quality of the OCR data that is used in survival analysis. METHODS AND DESIGN: Clinical information for 898 patients with squamous carcinoma of the head and neck including index tumor site, date of diagnosis, vital status, date of death, and cause of death from a prospective database at the Kingston Regional Cancer Center is compared to the same data elements in the OCR for the same patients. RESULTS: There is no statistically significant difference in disease-specific survival between the information from the two databases (log rank P = .89). The OCR captured and correctly assigned index tumor site for 81.4% (detection rate). The site assignment was accurate 90.9% of the time (confirmation rate), there was agreement on vital status (dead vs. alive) for all but one patient, and there was excellent agreement on date of death. However, cause of death (cancer vs. noncancer) based on death certificates had a 31% error rate. CONCLUSION: Researchers can be confident in the survival analysis generated from data in this registry, but need to be aware of potential sources of error.
BACKGROUND AND OBJECTIVES: The Ontario Cancer Registry (OCR) is a population-based tumor registry created to provide data for epidemiologic research and for cancer surveillance. Recently it has been used for health services research. The objective of this project was to assess the quality of the OCR data that is used in survival analysis. METHODS AND DESIGN: Clinical information for 898 patients with squamous carcinoma of the head and neck including index tumor site, date of diagnosis, vital status, date of death, and cause of death from a prospective database at the Kingston Regional Cancer Center is compared to the same data elements in the OCR for the same patients. RESULTS: There is no statistically significant difference in disease-specific survival between the information from the two databases (log rank P = .89). The OCR captured and correctly assigned index tumor site for 81.4% (detection rate). The site assignment was accurate 90.9% of the time (confirmation rate), there was agreement on vital status (dead vs. alive) for all but one patient, and there was excellent agreement on date of death. However, cause of death (cancer vs. noncancer) based on death certificates had a 31% error rate. CONCLUSION: Researchers can be confident in the survival analysis generated from data in this registry, but need to be aware of potential sources of error.
Authors: Kevin M Gorey; Isaac N Luginaah; Emma Bartfay; Karen Y Fung; Eric J Holowaty; Frances C Wright; Caroline Hamm; Sindu M Kanjeekal; Madhan K Balagurusamy Journal: Dig Dis Sci Date: 2010-06-03 Impact factor: 3.199
Authors: S D MacNeil; K Liu; S Z Shariff; A Thind; E Winquist; J Yoo; A Nichols; K Fung; S Hall; A X Garg Journal: Curr Oncol Date: 2015-04 Impact factor: 3.677
Authors: Kevin M Gorey; Isaac N Luginaah; Emma Bartfay; Karen Y Fung; Eric J Holowaty; Frances C Wright; Caroline Hamm; Sindu M Kanjeekal Journal: Am J Public Health Date: 2010-03-18 Impact factor: 9.308
Authors: Kevin M Gorey; Isaac N Luginaah; Karen Y Fung; Emma Bartfay; Caroline Hamm; Frances C Wright; Madhan Balagurusamy; Eric J Holowaty Journal: J Am Board Fam Med Date: 2010 Jan-Feb Impact factor: 2.657