OBJECTIVE: To analyze and predict the trends of incidence and mortality rates of esophageal cancer in areas of Taihang Mountains, and explore the strategies for facilitating the reduction of the incidence and mortality of esophageal cancer. METHODS: The data were collected from Linxian and Cixian Counties registries between 1988-1997. The trends of the incidence and mortality rates for esophageal cancer had been fitted and predicted by the model of BP (Back Propagation) Neural Networks. Then Linqi Xiang in Linxian County was taken as an example, to determine the power for reducing incidence and mortality of esophageal cancer using endoscopic technology as an early detection and treatment method. RESULTS: There were slowly declining trends for both incidence and mortality rates during past 10 years in Taihang Mountains. The predicting rates of the esophageal cancer incidence in 2,002 are 115. 70/100,000 for male and 79.88/100,000 for female; mortality rates are 94.00/100,000 and 56.29/100,000 respectively. Both incidence and mortality rates a still in high level. But when using endoscopic technology as an early detection and treatment method, the incidence rate is nearly 1/3 of a control group and the power is 88.30% at the end of eight years. The mortality rate is 1/4 of the control group and power is 89.44% after five years intervention (both powers based on 0.05 significant levels). CONCLUSIONS: The incidence and mortality rates for esophageal cancer are still on high levels in Taihang Mountains. We should continue to enhance our preventive effort there. After using endoscopic technology as an early detection and treatment method, the incidence and mortality rates will be decreased markedly during 5 to 8 years. It is recommended to implement a large-scale secondary prevention strategy in these areas.
OBJECTIVE: To analyze and predict the trends of incidence and mortality rates of esophageal cancer in areas of Taihang Mountains, and explore the strategies for facilitating the reduction of the incidence and mortality of esophageal cancer. METHODS: The data were collected from Linxian and Cixian Counties registries between 1988-1997. The trends of the incidence and mortality rates for esophageal cancer had been fitted and predicted by the model of BP (Back Propagation) Neural Networks. Then Linqi Xiang in Linxian County was taken as an example, to determine the power for reducing incidence and mortality of esophageal cancer using endoscopic technology as an early detection and treatment method. RESULTS: There were slowly declining trends for both incidence and mortality rates during past 10 years in Taihang Mountains. The predicting rates of the esophageal cancer incidence in 2,002 are 115. 70/100,000 for male and 79.88/100,000 for female; mortality rates are 94.00/100,000 and 56.29/100,000 respectively. Both incidence and mortality rates a still in high level. But when using endoscopic technology as an early detection and treatment method, the incidence rate is nearly 1/3 of a control group and the power is 88.30% at the end of eight years. The mortality rate is 1/4 of the control group and power is 89.44% after five years intervention (both powers based on 0.05 significant levels). CONCLUSIONS: The incidence and mortality rates for esophageal cancer are still on high levels in Taihang Mountains. We should continue to enhance our preventive effort there. After using endoscopic technology as an early detection and treatment method, the incidence and mortality rates will be decreased markedly during 5 to 8 years. It is recommended to implement a large-scale secondary prevention strategy in these areas.
Authors: Ying Gao; Nan Hu; Xiao You Han; Ti Ding; Carol Giffen; Alisa M Goldstein; Philip R Taylor Journal: Cancer Epidemiol Date: 2011-08-16 Impact factor: 2.984
Authors: Zhang Guohong; Su Min; Wang Duenmei; Hu Songnian; Liu Min; Li Jinsong; Lin Hongbin; Zhang Feng; Tian Dongping; Yang Heling; Liu Zhicai; Lian Shiyong; Guo Quansheng; Li Xiaoyun; Gao Yuxia Journal: PLoS One Date: 2010-03-15 Impact factor: 3.240
Authors: Nan Hu; Chaoyu Wang; David Ng; Robert Clifford; Howard H Yang; Ze-Zhong Tang; Quan-Hong Wang; Xiao-You Han; Carol Giffen; Alisa M Goldstein; Philip R Taylor; Maxwell P Lee Journal: Cancer Res Date: 2009-07-07 Impact factor: 12.701