Appraising the quality of sub-Saharan African cancer registration systems that contributed to GLOBOCAN 2008: a review of the literature and critical appraisal. (February 2015) - Crocker-Buque, Tim; Pollock, Allyson M
Objective: To critically appraise the quality of sub-Saharan African cancer registration systems that submitted data to GLOBOCAN 2008 with respect to population coverage using publicly available information and to show the use of GLOBOCAN statistics in determining global health priorities. Design: Sources of cancer registration data for twenty-six sub-Saharan African cancer registries were identified from GLOBOCAN 2008 factsheets. Additional information was extracted from International Agency for Research on Cancer publications. A literature search was conducted to identify studies that reported additional information on data collection methods and provided 27 studies. The websites of the 10 largest funders of development assistance for health were searched for GLOBOCAN citations. Setting and participants: Twenty-six sub-Saharan African cancer registration systems submitting data to GLOBOCAN 2008 in relation to 21 countries. Main outcome measures: Information on 15 quality variables were extracted and compared with the international gold standard for cancer registration systems. Results: Population coverage of the cancer registries ranged from from 2.3% of the population in Kenya to 100% in The Gambia, with a heavy urban bias in all countries. However, 20 countries (300 million people) had no cancer registration systems. Nineteen of the 26 registries failed to meet more than five of the 15 quality criteria and only one country met more than 10. Seven of the 10 largest funders of development assistance for health cite GLOBOCAN statistics in support of policy priorities. Conclusions: GLOBOCAN 2008 estimates are based on data drawn from poor quality cancer registration systems, with limited or no population registry coverage. It is essential the GLOBOCAN 2012 estimates should provide information on the quality of the data collection and explain the limitations of the estimates. Development organisations and the World Health Organization need to take a more cautious approach when using these data to determine priorities and allocating resources.