Epidemiology and Health

Cohort Profile

Integrated database-based Screening Cohort for Asian Nomadic descendants in China (Scan-China): Insights on prospective ethnicity-focused cancer screening: Yuelin Yu, Liying Qiao, Jing Han, Weiwei Wang, Weiwei Kang, Yunjing Zhang, Shu Shang, Ruogu Meng, Lin Zhuo, Siyan Zhan, Yunfeng Xi, Shengfeng Wang; Epidemiol Health. 2023;45:e2023048. Published online April 18, 2023; DOI: https://doi.org/10.4178/epih.e2023048

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Abstract Summary PDF Supplementary Material: Abstract
Established in 2017, the Screening Cohort for Asian Nomadic descendants in China (Scan-China) has benefited over 180,000 members of a multi-ethnic population, particularly individuals of Mongolian descent compared with the general population (Han ethnicity), in the Inner Mongolia Autonomous Region, China. This cohort study aims to evaluate the effectiveness of cancer screening and serve as a real-world data platform for cancer studies. The 6 most prevalent cancers in China are considered—namely, breast, lung, colorectal, gastric, liver and esophageal cancer. After baseline cancer risk assessments and screening tests, both active and passive follow-up (based on the healthcare insurance database, cancer registry, the front page of hospital medical records, and death certificates) will be conducted to trace participants’ onset and progression of cancers and other prevalent chronic diseases. Scan-China has preliminarily found a disproportionately lower screening participation rate and higher incidence/mortality rates of esophageal and breast cancer among the Mongolian population than among their Han counterparts. Further research will explore the cancer burden, natural history, treatment patterns, and risk factors of the target cancers.; Summary

Key Message
- Scan-China is the first and largest electronic health data (EHD)-integrated cancer screening program for the Mongolian ethnicity in Inner Mongolia. - Scan-China aims to evaluate the effectiveness of screening interventions, particularly on ethnic minorities, portray the natural history, explore risk factors and summarize treatment patterns and updated outcomes of prevalent tumors/other chronic diseases. - Scan-China database comprises baseline cancer risk assessment, screening tests results, active follow-up investigation for participants at high risk and EHD-integrated passive follow-up. Data sources for passive follow-up include healthcare insurance database, cancer registry, front page of hospital medical record and death certificates.

Original Article

Spatial analysis of tuberculosis treatment outcomes in Shanghai: implications for tuberculosis control: Jing Zhang, Xin Shen, Chongguang Yang, Yue Chen, Juntao Guo, Decheng Wang, Jun Zhang, Henry Lynn, Yi Hu, Qichao Pan, Zhijie Zhang; Epidemiol Health. 2022;44:e2022045. Published online May 1, 2022; DOI: https://doi.org/10.4178/epih.e2022045

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Abstract Summary PDF Supplementary Material: Abstract
OBJECTIVES
Tuberculosis (TB) treatment outcomes are a key indicator in the assessment of TB control programs. We aimed to identify spatial factors associated with TB treatment outcomes, and to provide additional insights into TB control from a geographical perspective.
METHODS
We collected data from the electronic TB surveillance system in Shanghai, China and included pulmonary TB patients registered from January 1, 2009 to December 31, 2016. We examined the associations of physical accessibility to hospitals, an autoregression term, and random hospital effects with treatment outcomes in logistic regression models after adjusting for demographic, clinical, and treatment factors.
RESULTS
Of the 53,475 pulmonary TB patients, 49,002 (91.6%) had successful treatment outcomes. The success rate increased from 89.3% in 2009 to 94.4% in 2016. The successful treatment outcome rate varied among hospitals from 78.6% to 97.8%, and there were 12 spatial clusters of poor treatment outcomes during the 8-year study period. The best-fit model incorporated spatial factors. Both the random hospital effects and autoregression terms had significant impacts on TB treatment outcomes, ranking 6th and 10th, respectively, in terms of statistical importance among 14 factors. The number of bus stations around the home was the least important variable in the model.
CONCLUSIONS
Spatial autocorrelation and hospital effects were associated with TB treatment outcomes in Shanghai. In highly-integrated cities like Shanghai, physical accessibility was not related to treatment outcomes. Governments need to pay more attention to the mobility of patients and different success rates of treatment among hospitals.; Summary

Key Message
Tuberculosis treatment outcomes, a key indicator in the assessment of TB control programs, were associated with spatial autocorrelation and hospital effects in Shanghai; however, they were not associated with physical accessibility to hospitals.

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