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OBJECTIVE: As a malignant tumour with a very high mortality rate, the incidence of pancreatic cancer is on the rise globally, but the long-term trend at the provincial level in China is not yet clear. This study aimed to investigate the trend of pancreatic cancer incidence in Jiangsu Province from 2009 to 2019 and to predict pancreatic cancer incidence from 2020 to 2030. STUDY DESIGN: Descriptive study. METHODS: Data on pancreatic cancer incidence in Jiangsu Province were obtained from the Jiangsu Cancer Registry. Trends in pancreatic cancer incidence from 2009 to 2019 were examined based on the Joinpoint regression model. Age-period-cohort (APC) models were introduced to estimate the independent effects of age, period, and cohort on the incidence of pancreatic cancer and to project pancreatic cancer incidence from 2020 to 2030. RESULTS: From 2009 to 2019, the number of pancreatic cancer cases in Jiangsu Province increased from 1146 to 2088, and the age-standardized incidence rate (ASIR) increased from 4.59 to 5.64 per 100,000 people. In 2019, the ASIR was higher in males than in females, and the ASIR was higher in urban areas than in rural areas. The APC analysis also showed that the age effect was the most important factor influencing pancreatic cancer incidence in Jiangsu Province. Predictions suggest that pancreatic cancer incidence will continue to increase from 2020 to 2030. CONCLUSIONS: From 2009 to 2019, the pancreatic cancer incidence in Jiangsu Province showed an increasing trend. The incidence rate is higher among males and urban residents. It is expected that the incidence of pancreatic cancer will continue to increase in the next decade. Therefore, pancreatic cancer prevention and control efforts should continue to focus on older adults and males. This study develops an advanced provincial prediction model, which provides a quantitative basis for allocating screening resources to high-risk populations and provides a reference paradigm for cancer prevention and control strategies in other developing countries undergoing industrialization.
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Yu et al. (2025) studied this question.
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