干预性队列研究的偏倚控制及其在中医领域的特殊性
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  • 英文篇名:Bias Control of Interventional Cohort Study and the Particularity in the Field of Traditional Chinese Medicine
  • 作者:张彤 ; 何文婷 ; 费宇彤 ; 张颖 ; 杨宇飞
  • 英文作者:ZHANG Tong;HE Wenting;FEI Yutong;ZHANG Ying;YANG Yufei;Xiyuan Hospital,China Academy of Chinese Medical Sciences;Xinjiang Uygur Autonomous Region Hospital of Traditional Chinese Medicine;Evidence-Based Medicine Center,Beijing University of Chinese Medicine;
  • 关键词:干预性队列研究 ; 偏倚 ; 真实世界研究 ; 方法学
  • 英文关键词:intervention cohort study;;bias;;real-world research;;methodology
  • 中文刊名:ZZYZ
  • 英文刊名:Journal of Traditional Chinese Medicine
  • 机构:中国中医科学院西苑医院;新疆维吾尔自治区中医医院;北京中医药大学循证医学中心;
  • 出版日期:2019-06-02
  • 出版单位:中医杂志
  • 年:2019
  • 期:v.60
  • 基金:国家重点研发计划(2017YFC1700604);; 首都卫生发展科研专项(2016-1-4171)
  • 语种:中文;
  • 页:ZZYZ201911006
  • 页数:5
  • CN:11
  • ISSN:11-2166/R
  • 分类号:28-32
摘要
作为真实世界研究方法之一,干预性队列研究具有较好的外部真实性,其证据级别仅次于随机对照试验,但最大的争议是偏倚。从研究设计、实施和统计分析的角度探讨如何控制干预性队列研究的常见偏倚。对于选择性偏倚,强调研究者的角色依然是观察者,不应干涉受试者入组意愿;清晰地界定暴露因素及强度有助于研究者判断受试者的最终暴露归属;部分特殊情况下适当采用随机化原则可减少选择性偏倚发生;可采用匹配法增加组间均衡性。对于信息性偏倚,建议采用客观、量化的指标收集资料,若难以实现,则采用"盲法"收集;在广泛收集资料的同时,需注意内容清晰易懂且不可过于繁琐,以免造成不应答偏倚。对于混杂偏倚,需要设置适当、清晰的纳入排除标准,排除已明确的混杂因素;在分析阶段,校正分析、亚组分析、多元回归分析、倾向性评分等都可用于控制偏倚。此外,中医药的干预性队列研究有其自身的特殊性,选择分中心时需注意不同地区的搭配及中医院、西医院及综合医院的搭配等。期待通过控制偏倚、优化设计以增加干预性队列研究的内部真实性及证据级别,使研究者在面对中医治疗这样个体化强、干预体系复杂、无法随机化、存在伦理学问题等情况下,转换研究思路,让更多患者因临床试验获益。
        As a real-world study,interventional cohort study has good external authenticity,whose evidence level is lower only than randomized controlled trials(RCTs),but its greatest controversy is bias. This paper discussed how to control common biases from the perspective of research design,implementation and statistical analysis. In controlling selective bias,the author emphasizes that the researcher is an observer and should not interfere with the intervention assignment. Exposure factors and intensity should be clearly defined to help researchers to determine the final exposure attribution of subjects. In some special cases,the randomization principle can reduce the occurrence of selective bias. Matching method can increase the balance between groups. In controlling information bias,it is suggested to use objective and quantitative indicators to collect data. If this is difficult to achieve,then "blinded"data collection method shall be used. For wide collection of information,the content should be clear and easy to understand,in order to avoid too cumbersome to create non-response bias. In controlling compounding bias,it is necessary to properly and clearly set the inclusion and exclusion criteria. The clear confounding factors can be excluded to reduce the occurrence of confounding bias. In the analysis phase,the correction analysis,subgroup analysis,multivariate regression analysis,and propensity scores are commonly used for controlling bias. In addition,the interventional cohort study of traditional Chinese medicine has its own particularity. When choosing sub-centers,researchers should focus on the match of different regions,as well as traditional Chinese medicine hospitals,western medicine hospitals and general hospitals. The author expects to improve the internal authenticity and evidence level of interventional cohort studies by controlling bias and optimizing design. Researchers can change research ideas in case of such individualized and complicated intervention systems like traditional Chinese medicine treatment,which does not allow randomization,and often with ethical issues,and let more patients benefit from clinical trials.
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