This paper focuses on the application of health big data in cancer screening. Firstly, the sources and characteristics of health big data are introduced, then the commonly used epidemiological designs and analytical techniques in hospital-based cancer screening studies are summarized and the application scenarios of such studies are described. Finally, the challenges and future development in the application of health big data are analyzed to provide reference for the future studies.

Objective:To investigate the value of a deep learning radiomics (DLR) nomogram model based on intra-tumoral and peri-tumoral MRI features for differentiating IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.Methods:This was a case-control study. The clinical and imaging data of 233 patients pathologically confirmed with either IgG4-ROD or orbital MALT lymphoma were retrospective collected between January 2020 and December 2024 from the Second Hospital of Jilin University (Center 1) and Beijing Tongren Hospital, Capital Medical University (Center 2). Patients from Center 1 ( n=158) were used as the training cohort, while those from Center 2 ( n=75) served as the validation cohort. Among the cases, 102 were IgG4-ROD (70 in training, 32 in validation) and 131 were orbital MALT lymphoma (88 in training, 43 in validation). Univariate and multivariate logistic regression analyses were used to identify independent clinical imaging predictors and build a clinical imaging model. Based on T 1WI, T 2WI, and diffusion weighted images, intra-tumoral regions were manually delineated, a 2 mm peri-tumoral margin was automatically generated, and both regions were combined as a single region of interest for radiomics feature extraction. Deep learning features were extracted using a ResNet-50 backbone, and after feature selection and dimensionality reduction, a DLR model was constructed. The clinical imaging features and DLR features were integrated to build a combined nomogram model. Model performance in differentiating IgG4-ROD from orbital MALT lymphoma was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. The area under the curve (AUC) were compared using the DeLong test. Results:Bilateral orbital involvement ( OR=1.983, 95% CI 1.166-2.843, P=0.046) and extraocular muscle involvement ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as independent predictors for distinguishing IgG4-ROD from orbital MALT lymphoma and were used to construct the clinical model. Fourteen features (9 radiomics and 5 deep learning features) were selected for the DLR model, and a nomogram was developed. In the training set, the AUCs for the clinical model, DLR model, and nomogram were 0.762 (95% CI 0.712-0.812), 0.865 (95% CI 0.822-0.908), and 0.943 (95% CI 0.909-0.953), respectively. In the validation set, the AUCs were 0.733 (95% CI 0.675-0.791), 0.823 (95% CI 0.762-0.884), and 0.924 (95% CI 0.902-0.958), respectively. The nomogram showed significantly higher AUCs than those of the clinical and DLR models alone (training set: Z=3.92, 2.87, P0.001, P=0.004; validation set: Z=3.25, 2.46, P=0.001, 0.014). Calibration curves indicated good agreement between predicted and actual IgG4-ROD incidence, and decision curve analysis demonstrated the highest net benefit for the nomogram. Conclusion:A nomogram that incorporates both intra-tumoral and peri-tumoral DLR features and clinical imaging characteristics demonstrates excellent performance in distinguishing IgG4-ROD from orbital MALT lymphoma.

This paper focuses on the application of health big data in cancer screening. Firstly, the sources and characteristics of health big data are introduced, then the commonly used epidemiological designs and analytical techniques in hospital-based cancer screening studies are summarized and the application scenarios of such studies are described. Finally, the challenges and future development in the application of health big data are analyzed to provide reference for the future studies.

Objective:To investigate the value of a deep learning radiomics (DLR) nomogram model based on intra-tumoral and peri-tumoral MRI features for differentiating IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.Methods:This was a case-control study. The clinical and imaging data of 233 patients pathologically confirmed with either IgG4-ROD or orbital MALT lymphoma were retrospective collected between January 2020 and December 2024 from the Second Hospital of Jilin University (Center 1) and Beijing Tongren Hospital, Capital Medical University (Center 2). Patients from Center 1 ( n=158) were used as the training cohort, while those from Center 2 ( n=75) served as the validation cohort. Among the cases, 102 were IgG4-ROD (70 in training, 32 in validation) and 131 were orbital MALT lymphoma (88 in training, 43 in validation). Univariate and multivariate logistic regression analyses were used to identify independent clinical imaging predictors and build a clinical imaging model. Based on T 1WI, T 2WI, and diffusion weighted images, intra-tumoral regions were manually delineated, a 2 mm peri-tumoral margin was automatically generated, and both regions were combined as a single region of interest for radiomics feature extraction. Deep learning features were extracted using a ResNet-50 backbone, and after feature selection and dimensionality reduction, a DLR model was constructed. The clinical imaging features and DLR features were integrated to build a combined nomogram model. Model performance in differentiating IgG4-ROD from orbital MALT lymphoma was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. The area under the curve (AUC) were compared using the DeLong test. Results:Bilateral orbital involvement ( OR=1.983, 95% CI 1.166-2.843, P=0.046) and extraocular muscle involvement ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as independent predictors for distinguishing IgG4-ROD from orbital MALT lymphoma and were used to construct the clinical model. Fourteen features (9 radiomics and 5 deep learning features) were selected for the DLR model, and a nomogram was developed. In the training set, the AUCs for the clinical model, DLR model, and nomogram were 0.762 (95% CI 0.712-0.812), 0.865 (95% CI 0.822-0.908), and 0.943 (95% CI 0.909-0.953), respectively. In the validation set, the AUCs were 0.733 (95% CI 0.675-0.791), 0.823 (95% CI 0.762-0.884), and 0.924 (95% CI 0.902-0.958), respectively. The nomogram showed significantly higher AUCs than those of the clinical and DLR models alone (training set: Z=3.92, 2.87, P0.001, P=0.004; validation set: Z=3.25, 2.46, P=0.001, 0.014). Calibration curves indicated good agreement between predicted and actual IgG4-ROD incidence, and decision curve analysis demonstrated the highest net benefit for the nomogram. Conclusion:A nomogram that incorporates both intra-tumoral and peri-tumoral DLR features and clinical imaging characteristics demonstrates excellent performance in distinguishing IgG4-ROD from orbital MALT lymphoma.

Objective:To estimate the lung cancer disease burden of residents caused by indoor radon exposure in living rooms in China, and to provide scientific basis for improving radon prevention and control policies and measures.Methods:Based on the data from the national indoor radon monitoring survey, the study of lung cancer caused by indoor radon, and the basic data such as population and smoking, the attributable burden of disease calculation method was used to estimate the disease burden of lung cancer caused by indoor radon in China.Results:In 2018, it was estimated that the years of life lost due to premature death (YLL), years of life lost due to health disability (YLD) and disability-adjusted life years (DALY) due to indoor radon exposure were 5.109 3 million, 0.052 6 million and 5.161 9 million, respectively. DALY was highest in the 50-54 age group. The disease burden of indoor radon-induced lung cancer in smoking men was more than 9 times that of smoking women, and the disease burden of lung cancer in non-smoking women was more than 5 times that of non-smoking men. Smoking is closely related to the disease burden of indoor radon-induced lung cancer.Conclusions:Indoor radon exposure is a major environmental risk factor associated with lung cancer burden in China. The health hazards of indoor radon require more attention and improved policy measures to address this challenge.

Objective:To investigate the correlation between RYR1 gene and the development of gastric cancer,as well as the mechanism of RYR1 in promoting the progression of gastric cancer.Methods:We analyzed gastric cancer data from TCGA and conducted high-throughput targeted sequencing and transcriptome sequencing on 81 gastric cancer tissue samples at Tianjin Medical University Cancer Institute&Hos-pital(TJMUCH)from December 2010 to December 2012.We collected clinicopathological data,compared the correlation between RYR1 mutations and expression levels,and analyzed the impact of RYR1 on the prognosis of patients with gastric cancer.Additionally,we explored the underlying molecular mechanism to study its role in promoting the development of gastric cancer by generating stable cell lines overex-pressing RYR1.Results:In TCGA gastric cancer patients,the mutation rate of RYR1 in Asian population was higher than that in others popula-tion(12.68%vs.8.13%).In gastric cancer patients from TJMUCH,RYR1 mutations ranked ninth in frequency,with a mutation rate of 33.33%.Mutations in RYR1 were negatively correlated with RYR1 expression(P=0.006 9,P<0.000 1).Patients with high RYR1 expression had significantly worse overall survival than those with low RYR1 expression(P=0.009 0,P=0.042 0).Overexpression of RYR1 promoted prolifera-tion,migration,invasion and reduced apoptosis of gastric cancer cell lines.Moreover,RYR1 overexpression was associated with decreased sensitivity to chemotherapeutic drugs in gastric cancer cells.Inhibiting RYR1-mediated calcium over-release could suppress malignant beha-viors and reverse chemoresistance.Conclusions:RYR1 had a high mutation rate in Asian gastric cancer patients and a significantly negative correlation with RYR1 mRNA levels.High RYR1 expression serves as a novel prognostic predictive marker for gastric cancer.RYR1 overex-pression promoted malignant progression of gastric cancer and chemoresistance by increasing the release of calcium ions from the endo-plasmic reticulum.Thus,RYR1 inhibition can reduce the proliferation,migration,and invasion of gastric cancer cells and reverse chemores-istance,which highlights potential combination therapies for gastric cancer.

Objective:To estimate the lung cancer disease burden of residents caused by indoor radon exposure in living rooms in China, and to provide scientific basis for improving radon prevention and control policies and measures.Methods:Based on the data from the national indoor radon monitoring survey, the study of lung cancer caused by indoor radon, and the basic data such as population and smoking, the attributable burden of disease calculation method was used to estimate the disease burden of lung cancer caused by indoor radon in China.Results:In 2018, it was estimated that the years of life lost due to premature death (YLL), years of life lost due to health disability (YLD) and disability-adjusted life years (DALY) due to indoor radon exposure were 5.109 3 million, 0.052 6 million and 5.161 9 million, respectively. DALY was highest in the 50-54 age group. The disease burden of indoor radon-induced lung cancer in smoking men was more than 9 times that of smoking women, and the disease burden of lung cancer in non-smoking women was more than 5 times that of non-smoking men. Smoking is closely related to the disease burden of indoor radon-induced lung cancer.Conclusions:Indoor radon exposure is a major environmental risk factor associated with lung cancer burden in China. The health hazards of indoor radon require more attention and improved policy measures to address this challenge.

Objective: To study the development of grip strength and its relationship with body weight, height and body composition in preschool children. Methods: Data was collected from 900 children aged 3-6 years in 4 preschools in Beijing during Sept. to Oct. of 2020. A questionnaire survey (birth weight, dietary and exercise), height, weight, bioelectrical impedance analysis of body composition and dominant hand grip strength tests were conducted. Partial correlational analysis, multivariate linear regression were used for association between grip strength and body composition. Results: The grip strength gradually increased with age, from (5.2±1.7) to (9.3±2.5)kg in boys ( F=57.93, P <0.01), and from (4.3±1.6) to (7.9±2.5)kg in girls ( F=48.77, P <0.01). Grip strength in boys were significant higher than that of girls ( t=6.42, P <0.01). The grip strength increased with weight status in boys ( F=5.35, P <0.01), with highest in obese group, followed by overweight and normal weight group. After adjusted for height, weight and birth weight, as well as maternal education, food consumption during the past week, grip strength in boys was positively correlated with fat free mass, upper limb muscle mass ( r=0.11, 0.09, P <0.05), and negatively correlated with body fat mass ( r=-0.18, P <0.05). Grip strength in girls was negatively correlated with body fat mass, and positively correlated with fat free mass ( r= -0.09, 0.09, P <0.05). Grip strength varied significantly by age, fat free mass and upper muscle mass in boys ( F=66.75, P < 0.01), and by age and fat free mass in girls ( F=150.81, P <0.01). Conclusion The grip strength can partially reflect changes in fat free mass for boys and girls, it also reflect changes in upper limb muscle mass for boys. Increases in fat free mass helps grip strength improvement.

Objective:To explore the status of early essential newborn care (EENC) implementation in four counties in western China.Methods:Based on the 18 counties from "safety newborn project", which was jointly launched by the National Health Commission (NHC) of China and United Nations Children's Fund, one county was randomly selected from Ningxia Hui Autonomous Region, and Guizhou, Sichuan and Qinghai Province, respectively (Longde county, Qinglong county, Tongjiang county, and Tongren county). Then one or two county-level birth facilities were randomly selected from each county for the field investigation from December 2020 to April 2021. Information of EENC core practice implementation was collected through questionnaires for mother-newborn dyads, and interviewees' experiences, attitudes, and needs for EENC implementation were obtained through focus group discussion and in-depth interviews with mothers. SAS 9.4 and NVivo 12.0 were used for quantitative and qualitative data analysis, then the results were integrated.Results:A total of 599 questionnaires for mother-newborn dyads were collected from the four counties, and 45 health staff and 15 mothers were interviewed. The proportion of participants with skin-to-skin contact (SSC) ≥90 min was the highest in Qinglong County, Guizhou Province (90.0%, 95% CI:85.2%-94.8%), followed by Tongjiang County, Sichuan Province (83.6%, 95% CI:77.7%-89.5%). The highest rate of early breastfeeding initiation was observed in Tongren County, Qinghai Province (99.3%, 95% CI:97.8%-100.0%). The positive experience of SSC for mothers were mainly from the promotion of happiness and early breastfeeding. Applied no medicine to the end of the umbilical cord, neonatal routine eye care, and vitamin K 1 administration were successfully promoted in the four counties, which gradually became a norm. However, some respondents still had doubts about SSC and applying no medicine to the end of the umbilical cord. Conclusions:Core practices recommended in EEEC were successfully introduced to the project counties despite concerns about certain practices from some medical staff and mothers. Further dissemination and training for EENC were needed to promote the scale-up of EENC in China.

Objective:To examine the trend of stroke disease burden and its main risk-attributable factors in China and regions with different Socio-Demographic Index (SDI) from 1990 to 2017.Methods:With 2017 Global Burden of Disease (GBD) data, years lived with disability (YLDs), years of life lost (YLLs) and disability-adjusted of life years (DALYs) were applied to describe the disease burden and major risk factors of stroke in China and different SDI regions from 1990 to 2017, and to analyze the changing trend of the disease burden and major risk factors of stroke.Results:From 1990 to 2017, the YLD crude rate, YLL crude rate and DALY crude rate for stroke in China showed an increasing trend and the rate of change was 126.5%, 14.6%, and 24.4%, respectively. In 2017, the YLD crude rate, YLL crude rate and DALY crude rate for stroke in China were 502.6 per 100 000, 2 633.1 per 100 000 and 3 135.7 per 100 000, respectively. Among them, the YLD crude rate, YLL crude rate, and DALY crude rate of stroke were the highest in the ≥70 age group, which were 2 617.2 per 100 000, 16 789.4 per 100 000 and 19 406.6 per 100 000, respectively. The YLD crude rate in male was 475.5 per 100 000, which was slightly lower than that of female (530.9 per 100 000), while the DALY crude rate and YLL crude rate for stroke were 3 657.1 per 100 000 and 3 181.7 per 100 000, respectively, which were significantly higher than that of female (2 591.8 per 100 000 and 2 060.9 per 100 000). Compared with regions with different SDI, the age standardized YLD rate, the age standardized YLL rate, the age standardized DALY rate in China were all at a high level. Among them, the age-standardized YLD rate increased from 286.2 per 100 000 to 374.5 per 100 000, with a rate of change of 30.9%; the age-standardized YLL rate decreased from 3 215.6 per 100 000 to 1 967.8 per 100 000, with a rate of change of -38.8%; the age-standardized DALY rate increased from 3 501.8 per 100 000 to 2 342.3 per 100 000, with a rate of change of -33.1%. The top five risk factors for stroke in China were hypertension, excessive sodium intake, insufficient fruit intake, insufficient cereal intake, and smoking in 1990 and 2017. High Body-Mass Index and Alcohol Use′s rankings rose from the 9th and 10th in 1990 to the 6th and 7th in 2017, respectively.Conclusion:The burden of stroke disease in China is at a high level, and hypertension is the primary risk factor.