Radical gastrectomy with D2 lymphadenectomy has been widely performed as the standard surgery for patients with gastric cancer in major medical centers in China and abroad. However, the exact extent of lymph node dissection is still controversial. In the latest version of the Japanese Gastric Cancer Treatment Guidelines, No. 14v lymph nodes (along the root of the superior mesenteric vein) are again defined as loco-regional lymph nodes, and it is clarified that distal gastric cancer presenting with infra-pyloric regional lymph node (No.6) metastasis is recommended for D2+ superior mesenteric vein (No. 14v) lymph node dissection. To explore the relevance and clinical significance of No.6 and No.14v lymphadenectomy in radical gastric cancer surgery, a review of the national and international literature revealed that No.6 lymph node metastasis was associated with No.14v lymph node metastasis, that No.6 lymph node status was a valid predictor of No.14v lymph node negative status and false negative rate, and that for gastric cancer patients with No. 14v lymph node negative and No.6 lymph node positive, the dissection of No.14v lymph node may also have some significance. The addition of No. 14v lymph node dissection in radical gastrectomy is safe, but it is more important to distinguish the patients who can benefit from it. Professor Liang Han of Tianjin Medical University Cancer Hospital is currently leading a multicenter, large-sample, prospective clinical trial (NCT02272894) in China, which is expected to provide higher level evidence for the clinical significance of lymph node dissection in No.14v.
Humans ; Stomach Neoplasms/pathology* ; Lymphatic Metastasis/pathology* ; Prospective Studies ; Retrospective Studies ; Lymph Nodes/pathology* ; Lymph Node Excision ; Gastrectomy ; Multicenter Studies as Topic

Large cohort study gained its popularity in biomedical research and demonstrated its application in exploring disease etiology and pathogenesis, improving the prognosis of disease, as well as reducing the burden of diseases. Data science is an interdisciplinary field that uses scientific methods from computer science and statistics to extract insights or knowledge from data in a specific domain. The results from the combination of the two would provide new evidence for developing the strategies and measures on disease prevention and control. This review included a brief introduction of data science, descriptions on characteristics of large cohort data according to the development of the study design, and application of data science at each stage of a large cohort study, as well as prospected the application of data science in the future large cohort studies.
Cohort Studies ; Data Science ; Interdisciplinary Studies

Precision medicine became the key strategy in development priority of science and technology in China. The large population-based cohorts become valuable resources in preventing and treating major diseases in the population, which can contribute scientific evidence for personalized treatment and precise prevention. The fundamental question of the achievements above, therefore, is how to construct a large population-based cohort in a standardized way. The Chinese Preventive Medicine Association co-ordinated experienced researchers from Peking University and other well-known institutes to write up two group standards Technical specification of data processing for large population-based cohort study (T/CPMA 001-2018) and Technical specification of data security for large population-based cohort study (T/CPMA 002-2018), on data management. The standards are drafted with principles of emphasizing their scientific, normative, feasible, and generalizable nature. In these two standards, the key principles are proposed, and technical specifications are recommended in data standardization, cleansing, quality control, data integration, data privacy protection, and database security and stability management in large cohort studies. The standards aim to guide the large population-based cohorts that have been or intended to be established in China, including national cohorts, regional population cohorts, and special population cohorts, hence, to improve domestic scientific research level and the international influence, and to support decision-making and practice of disease prevention and control.
China ; Cohort Studies ; Delivery of Health Care ; Humans ; Population Surveillance ; Quality Control ; Reference Standards

Objective: To describe the genetic structure of populations in different areas of China, and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies. Methods: By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB), we performed principal components analysis to extract the first and second principal components of the samples for the component two-dimensional diagram generation, and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China. Based on the CKB cohort data, a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated; and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated. Results: There were significant genetic structure differences in different areas of China. Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area. The first principal component corresponds to the latitude of different areas, and the second principal component corresponds to the longitude of different areas. The generated simulation data showed high false positive rate (λ=1.16), even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed, λ could not be effectively controlled (λ>1.05); while, by using a mixed linear model adjusting for the kinship matrix, λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ=0.99). Conclusions: There were large differences in genetic structure among populations in different areas of China. In molecular epidemiology studies, bias caused by population genetic structure needs to be carefully treated. For large cohort data with complex genetic structure and extensive kinship, it is necessary to use a mixed linear model for association analysis.
China ; Genetic Structures ; Genome-Wide Association Study ; Humans ; Linear Models ; Principal Component Analysis

Objective: To evaluate the association of educational level with anthropometric measurements at different adult stages and their long-term changes in adults who participated in the second re-survey of China Kadoorie Biobank (CKB). Methods: The present study excluded participants who were aged >65 years, with incomplete or extreme measurement values, or with major chronic diseases at baseline survey or re-survey. The weight at age 25 years was self-reported. Body height, body weight and waist circumference at baseline survey (2004-2008) and re-survey (2013-2014) were analyzed. Results: The present study included 3 427 men and 6 320 women. Both body weight and waist circumference (WC) increased with age. From age 25 years to baseline survey (mean age 45.2±6.5), the mean weight change per 5-year was (1.70±2.63) kg for men and (1.27±2.10) kg for women. From baseline survey to re-survey (53.2±6.5), the mean changes per 5-year for body weight were (1.12±2.61) kg for men and (0.90±2.54) kg for women; and that for WC was (3.20±3.79) cm for men and (3.83±3.85) cm for women. Among women, low educational level was consistently associated with higher body mass index (BMI) and WC at age 25 years, baseline survey and re-survey. Among men, low educational level was associated with higher BMI at age 25 years. At baseline survey and re-survey, the educational level in men was not statistically associated with BMI; but men who completed junior or senior high school showed slight higher WC and increase of WC from baseline survey to re-survey than other male participants. Conclusions: Body weight and WC increased with age for both men and women. The associations of educational level with BMI and WC were different between men and women.
Adult ; Asian People/statistics & numerical data* ; Body Height ; Body Mass Index ; Body Weight ; China/epidemiology* ; Educational Status ; Female ; Humans ; Male ; Middle Aged ; Obesity/ethnology* ; Risk Factors ; Sex Distribution ; Waist Circumference/ethnology*

This paper summarizes the Risk of Bias of Individual Studies in Systematic Reviews of Health Care Interventions revised by the Agency for Healthcare Research and Quality (AHRQ) and introduces how to use Revman software make risk of bias graph or risk of bias summary. AHRQ tool can be used to evaluate following study designs: RCTs, cohort study, case-control study (including nested case-control), case series study and cross-sectional study. The tool evaluates the risk of bias of individual studies from selection bias, performance bias, attrition bias, detection bias and reporting bias. Each of the bias domains contains different items, and each item is available for the assessment of one or more study designs. It is worth noting that the appropriate items should be selected for evaluation different study designs instead of using all items to directly assess the risk of bias. AHRQ tool can be used to evaluate risk of bias individual studies when systematic reviews of health care interventions is including different study designs. Moreover, the tool items are relatively easy to understand and the assessment process is not complicated. AHRQ recommends the use of high, medium and low risk classification methods to assess the overall risk of bias of individual studies. However, AHRQ gives no recommendations on how to determine the overall bias grade. It is expected that future research will give corresponding recommendations.
Bias ; Evidence-Based Medicine/standards* ; Health Services Research ; Systematic Reviews as Topic

Objective: To examine the prevalence of 'healthy lifestyle' from data extracted from the China Kadoorie Biobank (CKB) of 0.5 million adults from ten areas across China. Methods: After excluding participants with self-reported histories of coronary heart disease, stroke or cancer, a total of 487 198 participants at baseline (2004-2008) and 22 604 participants at second survey (2013- 2014), were included for analysis. 'Healthy lifestyle' was defined as haing the following characteristics: a) never smoking or having stopped smoking for reasons other than illness; b) alcohol drinking <25 g/day (men)/<15 g/day (women); c) diet rich in vegetables, fruits, legumes and fish, but low in red meat; d) upper quarter of the physical activity level; e) body mass index of 18.5-23.9 kg/m(2) and waist circumstance <85 cm (men)/80 cm (women). We calculated the healthy lifestyle scores (HLS) by counting the number of all the healthy lifestyle factors, with a range from 0 to 6. Results: At baseline, prevalence rates of the above five healthy lifestyles (except physical activity) were 70.6%, 92.6%, 8.7%, 52.6% and 59.0%, respectively, with the mean HLS being 3.1±1.2. Most participants (81.4%) had2-4 healthy components, while only 0.7% (0.2% in men and 1.0% in women) of all the participants had all six healthy lifestyles. Participants who were women, at younger age, with more schooling and rural residents, were more likely to adhere to the healthy lifestyle. After ten years, the mean HLS showed a slight decrease. Conclusion: The prevalence of optimal lifestyles in Chinese adults appeared extremely low. Levels of 'healthy lifestyle' varied greatly among those populations with different socio-demographic characteristics across the ten areas in China.
Adult ; Asian People/statistics & numerical data* ; China ; Female ; Healthy Lifestyle ; Humans ; Life Style ; Male ; Prevalence ; Risk Factors

Objective: To investigate the utilization of reproductive health services and relating factors among internal migrant population in Beijing, Shanghai and Chongqing. Methods: A multi-stage cluster sampling method was adopted in this cross-sectional study, conducted in Beijing, Shanghai and Chongqing from August 2014 to August 2015. Standard methods on statistics and nonlinear canonical correlation were applied. Results: Out of the 6 545 internal migrant persons, 41.76% ever used the reproductive health services in the past year. Results from the nonlinear canonical correlation analysis revealed that the utilization of reproductive health services was correlated with the demographic features (=0.28, P<0.000 1) and characteristics of the population mobility (=0.21, P<0.000 1), respectively. For the above said demographic features, canonical variable L(1) which represented the demographic features was mainly determined by area, occupation and education attainment. Canonical variable M(1) that reflected the utilization of reproductive health services, was mainly determined by factors as free contraceptives, education on contraception/reproductive health, and pregnancy diagnosis/antenatal care. As for the characteristics of the population mobility, canonical variable U(1), which represented population mobility characteristics, was mainly determined by factors as purpose of migration, current pattern of residence and the length of annual stay in the area. Again, the canonical variable V(1), reflecting the use of reproductive health services was mainly determined by factors as free contraceptives, check-up on reproductive tract infection, education on contraception/reproductive health, and pregnancy diagnosis/antenatal care. Conclusions: The utilization of reproductive health services was low among the internal migrant population under study. Responsible departments for health and family planning in those cities should make internal migrants attach importance to reproductive health.
China ; Cities ; Cross-Sectional Studies ; Demography ; Female ; Health Care Surveys ; Humans ; Patient Acceptance of Health Care ; Pregnancy ; Reproductive Health Services ; Transients and Migrants

Objective: To study the relations between famine exposure and the risk of chronic diseases as diabetes mellitus, obesity, hypertension, coronary heart disease and stroke in the population of Harbin. Methods: Our data was collected from the baseline survey-the China Kadoorie Biobank project (CKB) in Harbin. Retrospective cohort study design was used. Related risks on chronic diseases including diabetes mellitus, obesity, hypertension, coronary heart disease and stroke, were compared among the famine exposed or non-exposed people, respectively by logistic analysis method. Results: After adjusted for factors as age, sex, physical activity, smoking, alcohol intake, diet, family history of diseases, it appeared that the factor 'famine exposure' had increased the risks of diseases as obesity (OR=1.204, 95%CI: 1.104-1.313, P<0.01), hypertension (OR=1.315, 95%CI: 1.210-1.429, P<0.01) and coronary heart disease (OR=1.495, 95%CI: 1.369-1.632, P<0.01). The lower the age of population being exposed to famine, the greater the risk of the development of all kinds of chronic diseases. Conclusions: Famine exposure appeared a risk factor for obesity, hypertension, and coronary heart disease. It is of great significance to ensure the life-long nutrition of the people, especially in the early and adolescent stages, to prevent obesity, hypertension, and coronary heart disease in their later lives.
Adolescent ; China/epidemiology* ; Chronic Disease/epidemiology* ; Coronary Disease/epidemiology* ; Diabetes Mellitus/epidemiology* ; Female ; Humans ; Hypertension/epidemiology* ; Obesity/epidemiology* ; Pregnancy ; Prenatal Exposure Delayed Effects/epidemiology* ; Retrospective Studies ; Socioeconomic Factors ; Starvation/epidemiology*

Objective: To describe the study design, the characteristics of participants as well as the pedigrees included in the baseline survey of Fujian Tulou Family Cohort Study. Methods: Fujian Tulou Family Cohort Study was a prospective open cohort study with a biological sample bank. A baseline survey was conducted in Tulou areas of Nanjing county in Fujian province from 2015 to 2018, including questionnaire survey, physical and biochemical indicators examinations, and blood sample collection in adults aged ≥18 years. In addition, family relationship of the participants was also recorded. The pedigree information of the juveniles under 18 years old were also collected. Results: The baseline survey included 2 727 individuals in two clans, of whom 2 373 (87.0%) were adults, and 2 126 participants completed questionnaires, physical examinations and biochemical tests. The average age of the 2 126 participants was (57.9±13.3) years, with 39.4% being males. The current smoking rates in male and female participants were 41.2% and 2.1%, respectively. The corresponding rates of current alcohol consumption were 19.0% and 2.6%. For common chronic diseases, the prevalence rates were 51.3% for hypertension, 9.7% for diabetes and 26.7% for hyperlipemia according to the self-reported disease diagnoses, health examination results and biochemical examination results in class Ⅱ or Ⅲ hospitals. Based on the family relationship information and genealogical data, 710 pedigrees were finally identified, consisting of 5 087 family members. The numbers of five, four, three, and two generations pedigrees were 3, 88, 238 and 381, respectively. The pairs of the first to the fifth degree relatives were 12 039, 2 662, 1 511, 202 and 31, respectively. Conclusion: The establishment of Fujian Tulou Family Cohort provides valuable resources for exploring the genetic risk factors, environmental risk factors and gene-environment interactions contributing to the risk of common chronic diseases.
Adolescent ; Adult ; Aged ; China/epidemiology* ; Chronic Disease/ethnology* ; Cohort Studies ; Diabetes Mellitus/ethnology* ; Family Health ; Female ; Gene-Environment Interaction ; Genetic Predisposition to Disease/ethnology* ; Humans ; Hyperlipidemias/ethnology* ; Hypertension/ethnology* ; Male ; Middle Aged ; Pedigree ; Prospective Studies ; Risk Factors ; Surveys and Questionnaires