Spatial co-occurrence of multiple cancers: a population-based study using national cancer registry data in China

Abstract

Abstract Background Showing the spatial co-occurrence of multiple types of cancers supports geographical targeting and prioritization, because different cancer types often share common causes. However, the variation in incidence between different cancer types and regional differences within each cancer pose a major challenge to etiological research. This study aimed to assess the spatial co-occurrence of multiple cancers in mainland China to accelerate the identification of causes and development of tailored prevention policies. Methods We obtained cancer incidence data for 2016 for 13 cancers from the China Cancer Registry Annual Report. We proposed a design framework to assess the spatial co-occurrence of multiple cancer types using Moran’s I, and identified the level of risk of co-occurrence by area. We used negative binomial regression to obtain the incidence rate ratio for three risk-level areas, and the population attributable fraction and expected excess cases to estimate the proportion of cancer incidence attributable in different risk areas. Results The high-risk areas (17.1%) for cancer co-occurrence were mainly in the east and northeast, the low-risk areas (30.7%) were mainly in the south, and medium-risk areas (52.2%) were evenly distributed throughout China. The incidence rate ratio (95% confidence interval) was 1.61 (1.53–1.69) for high-risk areas, and 1.19 (1.14–1.23) for medium-risk areas compared to low-risk areas. Most provinces had two to three grades of risk areas. Zhejiang had the highest proportion of high-risk areas (85.7%), and Hunan the highest proportion of low-risk areas (86.4%). The most frequently observed cancer co-occurrence patterns were lung and pancreatic in the 15 provinces with high-risk areas; leukemia, brain tumor, bone, and gallbladder cancer in the 30 provinces with medium-risk areas; and pancreatic, lung and stomach cancer in the 24 provinces with low-risk areas. The population attributable factor ranged from 7.6–37.9% for high-risk areas and 1.8–15.9% for medium-risk areas. There were 44,568 expected excess cases in all areas. The highest number of expected excess cases was in Jiangsu and the lowest in Tibet. Conclusion This research framework could help to locate areas at high risk of cancer co-occurrence and identify common risk factors, guiding the development of tailored prevention policies.