Development, validation, and evaluation of a risk assessment tool for personalized screening of gastric cancer in Chinese populations.

BACKGROUND: Effective risk prediction models are lacking for personalized endoscopic screening of gastric cancer (GC). We aimed to develop, validate, and evaluate a questionnaire-based GC risk assessment tool for risk prediction and stratification in the Chinese population. METHODS: In this three-stage multicenter study, we first selected eligible variables by Cox regression models and constructed a GC risk score (GCRS) based on regression coefficients in 416,343 subjects (aged 40-75 years) from the China Kadoorie Biobank (CKB, development cohort). In the same age range, we validated the GCRS effectiveness in 13,982 subjects from another independent Changzhou cohort (validation cohort) as well as in 5348 subjects from an endoscopy screening program in Yangzhou. Finally, we categorized participants into low (bottom 20%), intermediate (20-80%), and high risk (top 20%) groups by the GCRS distribution in the development cohort. RESULTS: The GCRS using 11 questionnaire-based variables demonstrated a Harrell's C-index of 0.754 (95% CI, 0.745-0.762) and 0.736 (95% CI, 0.710-0.761) in the two cohorts, respectively. In the validation cohort, the 10-year risk was 0.34%, 1.05%, and 4.32% for individuals with a low (≤ 13.6), intermediate (13.7~30.6), and high (≥ 30.7) GCRS, respectively. In the endoscopic screening program, the detection rate of GC varied from 0.00% in low-GCRS individuals, 0.27% with intermediate GCRS, to 2.59% with high GCRS. A proportion of 81.6% of all GC cases was identified from the high-GCRS group, which represented 28.9% of all the screened participants. CONCLUSIONS: The GCRS can be an effective risk assessment tool for tailored endoscopic screening of GC in China. Risk Evaluation for Stomach Cancer by Yourself (RESCUE), an online tool was developed to aid the use of GCRS.

Urban spatial epidemic simulation model: A case study of the second COVID-19 outbreak in Beijing, China.

The second COVID-19 outbreak in Beijing was controlled by non-pharmaceutical interventions, which avoided a second pandemic. Until mass vaccination achieves herd immunity, cities are at risk of similar outbreaks. It is vital to quantify and simulate Beijing's non-pharmaceutical interventions to find effective intervention policies for the second outbreak. Few models have achieved accurate intra-city spatio-temporal epidemic spread simulation, and most modeling studies focused on the initial pandemic. We built a dynamic module of infected case movement within the city, and established an urban spatially epidemic simulation model (USESM), using mobile phone signaling data to create scenarios to assess the impact of interventions. We found that: (1) USESM simulated the transmission process of the epidemic within Beijing; (2) USESM showed the epidemic curve and presented the spatial distribution of epidemic spread on a map; and (3) to balance resources, interventions, and economic development, nucleic acid testing intensity could be increased and restrictions on human mobility in non-epidemic areas eased.

Maternal mortality ratio in Jiangsu Province, China: recent trends and associated factors.

BACKGROUND: In recent years, births to older mothers and multiparous mothers have increased rapidly with the change of birth policy in China. And mothers of advanced age are more likely to have maternal complications and poor birth outcomes. We aimed to estimate the recent trends and underlying risk factors of maternal mortality. METHODS: In this systematic assessment, we used data from the National Maternal and Child Health Routine Reporting System (2013-2018), Jiangsu Provincial Maternal Mortality Surveillance System (2017-2018), the Integrated National Mortality Surveillance System (2018), City Statistical Yearbooks (2018), City Health Statistical Yearbooks (2018). The factors associated with maternal mortality ratio (MMR) were explored using the stepwise regression analysis and cluster analysis. RESULTS: The MMR maintained at low levels between 2013 and 2016 and there was a slight increase in maternal mortality after 2016 in Jiangsu province. With the implementation of the China's universal two child policies, the percentage of multiparous mothers ascended from 34.2% (95% confidence interval (CI) = 34.1-34.3%) in 2013 to 51.4% (95% CI = 51.3-51.6%) in 2018 (beta = 3.88, P < 0.001). Consistently, the percentage of advanced maternal age (≥ 35) increased from 8.4% (95% CI = 8.4-8.5%) in 2013 to 10.4% (95% CI = 10.3-10.4%) in 2018 (beta = 0.50, P = 0.012). And we found that the percentage of multiparous mothers and advanced maternal age among maternal deaths were higher than all pregnant women (P < 0.001). In the stepwise regression analysis, four risk factors were significantly associated with maternal mortality ratio (primary industry of gross domestic product (GDP), rate of delivery in maternal and child health hospital, rate of cesarean section and rate of low birth weight). As the results derived from cluster analysis, the relatively developed regions had lower preventable maternal mortality ratio (43.5% (95% CI = 31.2-56.7%) vs. 62.6% (95% CI = 52.3-72.0%), P = 0.027). CONCLUSIONS: Since the universal two child policy has been associated with changes in health related birth characteristics: women giving birth have been more likely to be multiparous, and more likely to be aged 35 and over. This somewhat magnifies the impact of differences in economic development and obstetric services on MMR. The findings based on prefecture level data suggest that interventions must target economic development, the health system and maternal risk factors in synergy. These approaches will be of great benefit to control or diminish environmental factors associated with preventable deaths and will effectively reduce MMR and narrow the gap among the different regions.

Pollution exacerbates China's water scarcity and its regional inequality.

Inadequate water quality can mean that water is unsuitable for a variety of human uses, thus exacerbating freshwater scarcity. Previous large-scale water scarcity assessments mostly focused on the availability of sufficient freshwater quantity for providing supplies, but neglected the quality constraints on water usability. Here we report a comprehensive nationwide water scarcity assessment in China, which explicitly includes quality requirements for human water uses. We highlight the necessity of incorporating water scarcity assessment at multiple temporal and geographic scales. Our results show that inadequate water quality exacerbates China's water scarcity, which is unevenly distributed across the country. North China often suffers water scarcity throughout the year, whereas South China, despite sufficient quantities, experiences seasonal water scarcity due to inadequate quality. Over half of the population are affected by water scarcity, pointing to an urgent need for improving freshwater quantity and quality management to cope with water scarcity.

Dynamic simulation of the optimal allocation of water resources via the introduction of integrated water environmental policies in Baoding, China.

With rapid industrialization and urbanization, regional water shortages and water quality deterioration have posed great challenges for the sustainable development of cities in North China, especially those with a large demand for agricultural irrigation water. Based on an input-output analysis, this paper develops a dynamic optimization model consisting of three sub-models and multiple constraint conditions to solve the water crisis of Baoding, a typical city experiencing water shortages and serious water pollution in North China. The water resource carrying capacity (WRCC) indicator is introduced in the analysis of the results to comprehensively assess the effect of integrated water environmental policies (IWEPs) from 2013 to 2025. In the optimal scenario, the annual chemical oxygen demand (COD) discharge and annual water demand in Baoding can be reduced by 2.6% and 0.6%, respectively, with an annual gross regional product (GRP) growth rate of 7.52%. The WRCC can be improved from moderately overloaded to weakly unsaturated, which indicates that water resources can meet the socioeconomic development requirements. The results demonstrate the effectiveness of the linear optimization model with input-output analysis in coordinating the relationships among water demand, water environment protection, and economic development, and the IWEPs provide an applicable reference for decision-makers in Baoding and other similar cities in North China to address deteriorating water systems.

Integrating of genomic and transcriptomic profiles for the prognostic assessment of breast cancer.

PURPOSE: To evaluate the prognostic effect of the integration of genomic and transcriptomic profiles in breast cancer. METHODS: Eight hundred and ten samples from the Cancer Genome Atlas (TCGA) data sets were randomly divided into the training set (540 subjects) and validation set (270 subjects). We first selected single-nucleotide polymorphism (SNPs) and genes associated with breast cancer prognosis in the training set to construct the prognostic prediction model, and then replicated the prediction efficiency in the validation set. RESULTS: Four SNPs and three genes associated with the prognosis of breast cancer in the training set were included in the prognostic model. Patients were divided into the high-risk group and low-risk group based on the four SNPs and three genes signature-based genetic prognostic index. High-risk patients showed a significant worse overall survival [Hazard Ratio (HR) 9.43, 95% confidence interval (CI) 3.81-23.33, P < 0.001] than the low-risk group. Compared to the model constructed with only gene expression, the C statistics for the signature-based genetic prognostic index [area under curves (AUC) = 0.79, 95% CI 0.72-0.86] showed a significant increase (P < 0.001). Additionally, we further replicated the prognostic prediction model in the validation set as patients in the high-risk group also showed a significantly worse overall survival (HR 4.55, 95% CI 1.50-13.88, P < 0.001), and the C statistics for the signature-based genetic prognostic index was 0.76 (95% CI 0.65-0.86). The following time-dependent ROC revealed that the mean of AUCs were 0.839 and 0.748 in the training set and the validation set, respectively. CONCLUSIONS: Our findings suggested that integrating genomic and transcriptomic profiles could greatly improve the predictive efficiency of the prognosis of breast cancer patients.