Objective:To analyze the incidence and mortality of pancreatic cancer in China from 1992 to 2021, and to explore the effects of age, period, and cohort on pancreatic cancer incidence and mortality.Methods:Data from the Global Burden of Disease Study (GBD) 2021 database were used to analyze the incidence and mortality of pancreatic cancer in China from 1992 to 2021. The Joinpoint software was applied to analyze the time trends of standardized incidence and mortality rates, and to calculate the average annual percentage change. An age-period-cohort model was constructed to analyze the effects of age, period, and birth cohort on the trends of pancreatic cancer incidence and mortality. The disease burden of pancreatic cancer deaths attributed to risk factors such as hyperglycemia and smoking was analyzed.Results:In 2021, the incidence of pancreatic cancer in China was 8.34/100 000, and the mortality rate was 8.41/100 000, representing increases of 150.45% and 145.19%, respectively, compared to 1992 (3.33/100 000 and 3.43/100 000) . By sex, the incidence (9.93/100 000) and mortality (9.91/100 000) rates in males in 2021 were higher than those in females (6.68/100 000 and 6.83/100 000) . From 1992 to 2021, the standardized incidence and mortality rates of pancreatic cancer in China showed upward trends, with average annual increases of 0.80% and 0.62%, respectively, both of which were statistically significant (both P<0.001) . Age effect results indicated a general increasing trend in pancreatic cancer incidence, with a steady rise in the 15-49 age group, a sharp increase after the age of 50, and a peak in the over 85 age group at 68.64/100 000. The mortality rate showed a slow increase in the 15-79 age group, with a marked rise and peak in the 80-84 age group at 196.51/100 000. Period effect results showed an overall upward trend in the period relative risk ( RR) for pancreatic cancer incidence, with the highest risk in 2017-2021 ( RR=1.09, 95% CI: 1.05-1.13, P=0.012) , compared to the reference period 2002-2006 ( RR=1) . The RR for pancreatic cancer mortality showed a fluctuating trend, with the highest risk in 2012-2016 ( RR=1.60, 95% CI: 1.07-2.38, P=0.021) , compared to the reference period 2002-2006 ( RR=1) . The results of cohort effect showed that the incidence and mortality risk of pancreatic cancer in China generally increased with the increase of years. With the 1952-1956 birth cohort as the reference cohort ( RR=1) , the incidence ( RR=1.18, 95% CI: 0.99-1.40, P=0.032) and mortality ( RR=1.63, 95% CI: 0.12-11.53, P=0.042) risk of pancreatic cancer were the highest in the 1987-1991 birth cohort, and showed decreasing trends after the 1992-1996 birth cohort. The proportion of pancreatic cancer deaths attributable to high blood glucose showed an increasing trend, while those attributable to smoking showed a decreasing trend. Conclusions:From 1992 to 2021, the standardized incidence and mortality rates of pancreatic cancer in China have continued to rise, with males having higher incidence and mortality rates than females. Age, period, and cohort all significantly influence the trends in pancreatic cancer incidence and mortality. The trend in pancreatic cancer deaths attributable to high blood glucose is increasing.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective To establish a method for the determination of 10-hydroxyl carbamazepine (MHD),which is an activity metabolite of oxcarbazepine in human serum. Methods Serum samples were detected by high performance liquid chromatography (HPLC) after being processed by methanol protein deposition.The chromatographic column was Agilent TC-C18 (4.6 mm × 250 mm, 5 μm), with the mobile phase of acetonitrile-10 mmol ? L-1 KH2 PO4 ( 33 : 67) at a flow rate of 1.0 mL?min-1 .The detection wavelength was 230 nm,and phenacetin was used as an internal standard. Results The average recovery range of low,middle and high (1.0,10.0,60.0 μg?mL-1 ) concentrations for MHD was from 100.3％ to 106.0％.The RSD of intra-day and inter-day was ≤5.8％ (n= 5) and ≤7.4％ (n= 5),respectively.The limit detection of analysis method was 0.1 μg?mL-1 .Regression equation was Y = 0.1308X+ 0.0679 ( r = 0.9966,n = 5). Serum samples remained stable at room temperature,freezing and freeze thawing condition. Conclusion This method is sensitive,accurate,simple and quick,and can be used for monitoring the oxcarbazepine metabolites MHD in serum for clinical and pharmacokinetic study.