Therese M-L Andersson1, Mark J Rutherford2,3, Tor Åge Myklebust4,5, Bjørn Møller4, Isabelle Soerjomataram3, Melina Arnold3, Freddie Bray3, D Max Parkin3,6, Peter Sasieni7, Oliver Bucher8, Prithwish De9, Gerda Engholm10, Anna Gavin11, Alana Little12, Geoff Porter13, Agnihotram V Ramanakumar14, Nathalie Saint-Jacques15, Paul M Walsh16, Ryan R Woods17, Paul C Lambert18,2. 1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. therese.m-l.andersson@ki.se. 2. Department of Health Sciences, University of Leicester, Leicester, UK. 3. Cancer Surveillance Section, International Agency for Research on Cancer (IARC/WHO), Lyon, France. 4. Cancer Registry of Norway, Institute of Population-based Cancer Research, Oslo, Norway. 5. Department of Research and Innovation, Møre and Romsdal Hospital Trust, Ålesund, Norway. 6. Nuffield Department of Population Health, University of Oxford, Oxford, UK. 7. King's College London, Clinical Trials Unit, London, UK. 8. Department of Epidemiology and Cancer Registry, CancerCare Manitoba, Winnipeg, MB, Canada. 9. Analytics and Informatics, Ontario Health (Cancer Care Ontario), Toronto, ON, Canada. 10. Surveillance and Pharmacoepidemiology, Danish Cancer Society Research Center, Copenhagen, Denmark. 11. Northern Ireland Cancer Registry, Queen's University Belfast, Northern Ireland, UK. 12. Cancer Institute NSW, Alexandria, NSW, Australia. 13. Canadian Partnership Against Cancer, Toronto, ON, Canada. 14. Research-Institute, McGill University Health Center, Montreal, QC, Canada. 15. Nova Scotia Health Authority Cancer Care Program, Registry & Analytics, Halifax, NS, Canada. 16. National Cancer Registry, Ireland, Cork, Ireland. 17. Cancer Control Research, BC Cancer, Vancouver, BC, Canada. 18. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Abstract
BACKGROUND: Data from population-based cancer registries are often used to compare cancer survival between countries or regions. The ICBP SURVMARK-2 study is an international partnership aiming to quantify and explore the reasons behind survival differences across high-income countries. However, the magnitude and relevance of differences in cancer survival between countries have been questioned, as it is argued that observed survival variations may be explained, at least in part, by differences in cancer registration practice, completeness and the availability and quality of the respective data sources. METHODS: As part of the ICBP SURVMARK-2 study, we used a simulation approach to better understand how differences in completeness, the characteristics of those missed and inclusion of cases found from death certificates can impact on cancer survival estimates. RESULTS: Bias in 1- and 5-year net survival estimates for 216 simulated scenarios is presented. Out of the investigated factors, the proportion of cases not registered through sources other than death certificates, had the largest impact on survival estimates. CONCLUSION: Our results show that the differences in registration practice between participating countries could in our most extreme scenarios explain only a part of the largest observed differences in cancer survival.
BACKGROUND: Data from population-based cancer registries are often used to compare cancer survival between countries or regions. The ICBP SURVMARK-2 study is an international partnership aiming to quantify and explore the reasons behind survival differences across high-income countries. However, the magnitude and relevance of differences in cancer survival between countries have been questioned, as it is argued that observed survival variations may be explained, at least in part, by differences in cancer registration practice, completeness and the availability and quality of the respective data sources. METHODS: As part of the ICBP SURVMARK-2 study, we used a simulation approach to better understand how differences in completeness, the characteristics of those missed and inclusion of cases found from death certificates can impact on cancer survival estimates. RESULTS: Bias in 1- and 5-year net survival estimates for 216 simulated scenarios is presented. Out of the investigated factors, the proportion of cases not registered through sources other than death certificates, had the largest impact on survival estimates. CONCLUSION: Our results show that the differences in registration practice between participating countries could in our most extreme scenarios explain only a part of the largest observed differences in cancer survival.
Authors: Citadel J Cabasag; Melina Arnold; Mark Rutherford; Aude Bardot; Jacques Ferlay; Eileen Morgan; Alana Little; Prithwish De; Elijah Dixon; Ryan R Woods; Nathalie Saint-Jacques; Sue Evans; Gerda Engholm; Mark Elwood; Neil Merrett; David Ransom; Dianne L O'Connell; Freddie Bray; Isabelle Soerjomataram Journal: Br J Cancer Date: 2022-03-02 Impact factor: 9.075
Authors: Fabian Gil; Adalberto Miranda-Filho; Claudia Uribe-Perez; N E Arias-Ortiz; M C Yépez-Chamorro; L M Bravo; Esther de Vries Journal: J Cancer Epidemiol Date: 2022-01-30