Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference ...Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference information for JE control and prevention. Methods Theoretically epidemiologic study was employed in the research process. Monthly incidence data on JE for the period from Jan 2005 to Sep 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang, Shaanxi province. An optimal SARIMA model was developed for JE incidence from 2005 to 2013 with the Box and Jenkins approach. This SARIMA model could predict JE incidence for the year 2014 and 2015. Results SARIMA （1, 1, 1） （2, 1, 1）12 was considered to be the best model with the lowest Bayesian information criterion, Akaike information criterion, Mean Absolute Error values, the highest R2, and a lower Mean Absolute Percent Error. SARIMA （1, 1, 1） （2, 1, 1）12 was stationary and accurate for predicting JE incidence in Xianyang. The predicted incidence, around 0.3/100 000 from June to August in 2014 with low errors, was higher compared with the actual incidence. Therefore, SARIMA （1, 1, 1） （2, 1, 1）12 appeared to be reliable and accurate and could be applied to incidence prediction. Conclusions The proposed prediction model could provide clues to early identification of the JE incidence that is increased abnormally （≥0.4/100 000）. According to the predicted results in 2014, the JE incidence in Xianyang will decline slightly and reach its peak from June to August.The authors wish to thank the staff from the CDCs from 13 counties of Xianyang, Shaanxi province, China, for their contribution to Japanese encephalitis cases reporting.展开更多
Objective: The aim of this study was to identify the correlation between the clinicopathological characteristics and recurrence in early gastric cancer (EGC), what's more, we attempt to look for a predictive bioma...Objective: The aim of this study was to identify the correlation between the clinicopathological characteristics and recurrence in early gastric cancer (EGC), what's more, we attempt to look for a predictive biomarker to predict and treat for re-currence of EGC. Methods: This study retrospectively analyzed 178 early gastric cancer patients who had the complete post-operative and follow-up medical records in the First Affiliated Hospital of Yangtze University (China) between January 1995 to December 2005. All of them were followed-up to December 2009 regularly. Computer tomography (CT), endoscopy, and single photon emission computed tomography (SPET-CT) were used to diagnose for recurrence of EGC. Immunohistochem-istry (IHC) and fluorescence in situ hybridization (FISH) were used for the detection of cerbB2. Chi-square test was applied to this study for statistics analysis. Results: Fourteen patients had recurrence. Eighteen patients were cerbB2-positive, including twelve recurrence patients and six norecurrence patients. Sex, tumor depth, and lymph node metastasis were related to the recurrence of EGC. Also, cerbB2-positive patients had the higher recurrence rate compared to the cerbB2-negative patients. Conclusion: Recurrence of EGC after curative resection can be predicted by using some clinicopathological characteristics. CerbB2 can be used as a predictive biomarker for recurrence of EGC.展开更多
基金Supported by the Youth Project of Shaanxi University of Chinese Medicine(2015QN05)
文摘Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference information for JE control and prevention. Methods Theoretically epidemiologic study was employed in the research process. Monthly incidence data on JE for the period from Jan 2005 to Sep 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang, Shaanxi province. An optimal SARIMA model was developed for JE incidence from 2005 to 2013 with the Box and Jenkins approach. This SARIMA model could predict JE incidence for the year 2014 and 2015. Results SARIMA （1, 1, 1） （2, 1, 1）12 was considered to be the best model with the lowest Bayesian information criterion, Akaike information criterion, Mean Absolute Error values, the highest R2, and a lower Mean Absolute Percent Error. SARIMA （1, 1, 1） （2, 1, 1）12 was stationary and accurate for predicting JE incidence in Xianyang. The predicted incidence, around 0.3/100 000 from June to August in 2014 with low errors, was higher compared with the actual incidence. Therefore, SARIMA （1, 1, 1） （2, 1, 1）12 appeared to be reliable and accurate and could be applied to incidence prediction. Conclusions The proposed prediction model could provide clues to early identification of the JE incidence that is increased abnormally （≥0.4/100 000）. According to the predicted results in 2014, the JE incidence in Xianyang will decline slightly and reach its peak from June to August.The authors wish to thank the staff from the CDCs from 13 counties of Xianyang, Shaanxi province, China, for their contribution to Japanese encephalitis cases reporting.
文摘Objective: The aim of this study was to identify the correlation between the clinicopathological characteristics and recurrence in early gastric cancer (EGC), what's more, we attempt to look for a predictive biomarker to predict and treat for re-currence of EGC. Methods: This study retrospectively analyzed 178 early gastric cancer patients who had the complete post-operative and follow-up medical records in the First Affiliated Hospital of Yangtze University (China) between January 1995 to December 2005. All of them were followed-up to December 2009 regularly. Computer tomography (CT), endoscopy, and single photon emission computed tomography (SPET-CT) were used to diagnose for recurrence of EGC. Immunohistochem-istry (IHC) and fluorescence in situ hybridization (FISH) were used for the detection of cerbB2. Chi-square test was applied to this study for statistics analysis. Results: Fourteen patients had recurrence. Eighteen patients were cerbB2-positive, including twelve recurrence patients and six norecurrence patients. Sex, tumor depth, and lymph node metastasis were related to the recurrence of EGC. Also, cerbB2-positive patients had the higher recurrence rate compared to the cerbB2-negative patients. Conclusion: Recurrence of EGC after curative resection can be predicted by using some clinicopathological characteristics. CerbB2 can be used as a predictive biomarker for recurrence of EGC.
