文章摘要
白宇鸽,徐玲,段学宁,刘荫华,叶京明,刘倩,程元甲,辛灵,王临虹,包鹤龄,余之刚,刘丽媛,王睿,石志国.中国乳腺癌专病队列研究:临床队列的设计与初步结果[J].中华流行病学杂志,2020,41(12):2046-2052
中国乳腺癌专病队列研究:临床队列的设计与初步结果
The Breast Cancer Cohort Study in Chinese Women: research design and preliminary results of clinical multi-center cohort
收稿日期:2020-05-07  出版日期:2020-12-25
DOI:10.3760/cma.j.cn112338-20200507-00694
中文关键词: 乳腺癌;精准医学;队列研究
英文关键词: Breast cancer;Precision medicine;Cohort study
基金项目:国家重点研发计划(2016YFC0901302);北京科技大学顺德研究生院科技创新专项资金(BK19CF010)
作者单位E-mail
白宇鸽 北京大学第一医院乳腺疾病中心 100034  
徐玲 北京大学第一医院乳腺疾病中心 100034 xuling_en@126.com 
段学宁 北京大学第一医院乳腺疾病中心 100034  
刘荫华 北京大学第一医院乳腺疾病中心 100034  
叶京明 北京大学第一医院乳腺疾病中心 100034  
刘倩 北京大学第一医院乳腺疾病中心 100034  
程元甲 北京大学第一医院乳腺疾病中心 100034  
辛灵 北京大学第一医院乳腺疾病中心 100034  
王临虹 中国疾病预防控制中心慢性非传染性疾病预防控制中心, 北京 100050  
包鹤龄 中国疾病预防控制中心慢性非传染性疾病预防控制中心, 北京 100050  
余之刚 山东大学第二医院, 济南 250033  
刘丽媛 山东大学第二医院, 济南 250033  
王睿 北京科技大学 100083  
石志国 北京科技大学 100083  
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中文摘要:
      目的 中国女性乳腺癌发病率持续升高,负担重。乳腺癌诊疗及相关预后研究必需的临床队列建设面临诸多瓶颈,国内乳腺癌大型队列研究相对匮乏,存在标准不统一、失访率较高、重复建设、无法共享等问题。本课题为改善我国目前大型临床队列研究面临的困难和问题,联合多家三级甲等医院,合作建立中国乳腺癌专病队列,为进行乳腺癌多中心临床队列研究提供数据平台和技术支撑。方法 乳腺癌标准化前瞻性队列专病队列的建立以循证医学证据为基础,通过专家论证建立乳腺癌队列标准化入组指标集,收集入组对象的基线信息、诊疗相关信息并采集生物标本。根据大型人群队列终点事件长期随访技术规范、数据安全及数据处理技术规范的要求,形成乳腺癌标准化前瞻性队列的诊疗及预后研究的随访体系。结果 基于标准化的数据集,利用北京科技大学的计算机学科优势,整合动态信息采集终端和社会网络等新兴信息技术手段改善依从性及智能数据质量控制方案,研发出了中国乳腺癌专病队列数据库,截至2020年2月临床队列数据库中纳入患者12 147名。队列建设过程中采集样本资源,并与山东大学牵头开展的生物样本库多中心质量控制体系及共享评价体系研究合作,构建了开放共享的生物样本库网络,形成了乳腺癌发生发展全链条的研究平台。结论 本研究随着“十三五”规划精准医学研究的实施,为乳腺癌精准诊疗提供了研究基础,为国家制定相关医学政策提供了数据支持。
英文摘要:
      Objective The incidence of breast cancer in Chinese women continues to rise. The large breast cancer cohort studies in China are relatively scarce. There are many bottlenecks in the construction of large clinical cohort for breast cancer diagnosis, treatment, and prognoses, such as inconsistent standards, high rates of lost follow-up, repeated construction, and inability to share. To better solving the difficulties and problems faced by large-scale clinical cohort research in China, this project will cooperate with several tertiary A hospitals to establish a breast cancer cohort in Chinese women. It also provides a data platform and technical support for breast cancer multi-center clinical cohort research. Methods Based on the evidence-based medicine and expert opinion and consensus, we established a breast cancer cohort standardized indicator set-recording baseline information, diagnosis and treatment-related information of the enrolled patients, and collecting biological specimens. According to the technical specification of long-term follow-up for the endpoint, data management, and data security and in the large population-based cohort study, a standardized follow-up system for the diagnosis, treatment, and prognosis of breast cancer prospective cohorts is formed. Results Based on standardized data sets and the computer discipline's advantage from the University of Science and Technology Beijing, we integrate the new information technology methods, including dynamic information collection terminals and social networks. Thus, the quality of control programs on compliance and intelligence data was improved, and a Chinese women breast cancer cohort database was developed. By February 2020, 12 147 patients were included in the clinical cohort database. Biological specimens' resources in cohort construction were collected and cooperated with Shandong University to research the multi-center quality control system and shared evaluation system of biobanks. Building an open and shared biobank network and forming a full chain of breast cancer research platform. Conclusion With the implementation of the "13th Five-Year Plan" precision medicine research, this study provides a research foundation for precision diagnosis and treatment of breast cancer and provides data support for the country to formulate relevant medical policies.
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