Drug safety signal detection in a regional healthcare database using the tree-based scan statistic and comparison to 3 other mining methods.

AIMS: To evaluate and compare the relative performance of the tree-based scan statistic (TreeScan) with the crude cohort study, Bayesian confidence propagation neural network (BCPNN) and Gamma Poisson Shrinker (GPS) in detecting statin-related adverse events (AEs) in an electronic healthcare database. METHODS: Data from a Chinese healthcare database from 2010 to 2016 were evaluated. We identified statin users based on prescription information in their out-/in-patient records, and AEs were defined according to the ICD-10 codes in patients' diagnosis records. TreeScan was applied to detect AE signals related to statin use and was compared with 3 other methods based on sensitivity, specificity, positive predictive value, negative predictive value, accuracy, the Youden index, area under the precision-recall curve and the area under the receiver operating characteristic curve. RESULTS: A total of 224 187 patients were enrolled and divided into 85 758 statin users and 138 429 nonusers. TreeScan generated 29 positive signals, of which 9 were known AEs. The sensitivities of TreeScan, BCPNN and GPS were all 69.2%, which was higher than that of the crude cohort study (46%). The specificity (82.3%), positive predictive value (31.0%), negative predictive value (95.9%), accuracy (81.0%), Youden index (51.5%) and area under the receiver operating characteristic curve (75.8%) of TreeScan were the highest among the 4 methods. CONCLUSION: TreeScan outperformed the crude cohort, BCPNN and GPS in detecting statin-related AEs in an electronic healthcare database. Therefore, it can be used as a complementary tool for other signal detection methods in drug safety surveillance.

A community-based survey on risk factors of type 2 diabetic kidney disease in Ningbo, China / 浙江大学学报·医学版

<p><b>OBJECTIVE</b>To investigate the prevalence and risk factors of diabetic nephropathy in Ningbo Yinzhou district.</p><p><b>METHODS</b>Nephropathy screening was conducted among patients with type 2 diabetes mellitus (T2DM) registered in Ningbo Yinzhou district. Demographic information, clinical examination information, diabetes complications and behavioral risk factors of enrolled patients were collected. Logistic regression model was used to identify possible risk factors for the occurrence of diabetic nephropathy.</p><p><b>RESULTS</b>Among 10 604 T2DM patients included in this study, there were 3744 cases of diabetic nephropathy(35.31%). Univariate analysis showed that gender, age, education level, diabetes duration, glycemic control, hypertension, stroke, smoking and waist circumference were associated with diabetic nephropathy (<0.05 or <0.01). Multivariate logistic regression analysis showed that male, elders, long diabetes duration, hypertension and smoking were independent risk factors of diabetic nephropathy (<0.05 or <0.01).</p><p><b>CONCLUSIONS</b>sDiabetic nephropathy is of high prevalence in T2DM patients. Male patients, elders, and those with long diabetes duration, hypertension and smoking habits are more likely to have diabetic nephropathy.</p>

Time-series analysis of particulate matter and daily hospital visits for coronary heart disease in Yinzhou district, Ningbo area / 浙江大学学报·医学版

To explore the association between particulate matter (PM) and daily hospital visits of coronary heart diseases in Ningbo.Daily data of hospital visits from January 2014 to June 2015 (516 days in total) were obtained from the Yinzhou Health Information System in Ningbo. Daily air pollution data for PM and meteorological data were collected from the database of Ningbo Environmental Monitoring Center and Ningbo Meteorological Bureau. Time-series analysis by quasi-Poisson generalized additive model was used to examine the association between air pollution and hospital visits for coronary heart diseases by adjustment of long-term trends, seasonal patterns and meteorological variables (temperature, humidity), and day of week.An increase of an IQR of PMaccounted for 1.98% (95%:-0.59%-4.63%) increase of hospital visits for coronary heart diseases. The associations between PMand hospital visits for coronary heart diseases among female and the elderly (≥75 years) were stronger (=2.70%,95%:0.01%-5.47%;=3.35%, 95%0.12%-6.69%). The effects of PMattenuated after adjustment for PMPMhad short-term effects on daily hospital visits for coronary heart diseases in Ningbo, and such association was stronger among female and the elderly.