摘要
目的运用专家共识法原理，初步制定“中国2017版罕见病调研清单”。方法采用“清单式”方法，在中国可公开获得的5个罕见病数据来源中初步遴选调研疾病。对疾病种类汇总、校对、去重，形成包含344种疾病的罕见病调研初步清单。通过组织两轮专家共识会，对罕见病相关病种进行投票、修正，最终形成“中国2017版罕见病调研清单”。结果根据投票结果，入选专家共识会讨论的344种罕见病中，建议删除病种54种，建议合并病种9对。对罕见病病种的中英文名称，经讨论306／344符合中英文命名规范。根据专家修改意见和建议，对罕见病调研清单进行修正，最终形成包括281种疾病的“中国2017版罕见病调研清单”。结论专家共识法充分结合了方法学的科学性和专家丰富的临床经验，在目前医疗卫生大数据战略和精准扶贫的大背景下，此前期工作符合目前我国罕见病全国范围内调研的整体研究思路。
Objective To preliminary formulated 2017 Chinese rare disease survey list by experts consensus. Methods By using checklist methods, we selected studied diseases from five availa ble rare disease data sources in China. By summarizing, proofreading, removing of duplicate data, the primary survey list with 344 diseases was formulated. By organizing two rounds of consensus conferences, experts voted and revised the survey list, then ultimately formulated 2017 Chinese rare disease survey list. Results According to the poll, in selected 344 rare diseases which were discussed in con- sensus conferences, 54 diseases were suggested to be deleted, 9 pairs of diseases were suggested to be incorporated. For Chinese and English names of these rare diseases, 306/344 diseases conform to no menclature by discussion. According to the experts＇ tips and advice, we revised the primary survey list and ultimately formulated 2017 Chinese rare disease survey list including 281 diseases. Conclusions Experts consensus combines the scientificity of methodology and clinical experience of experts. In the background of medical big data and targeted poverty alleviation, the early stage of study is in ac- cordance with the main stream of thought for the national survey of rate disease in China.
作者
石鑫淼
李岩
詹思延
王琳
王朝霞
刘徽
丁洁
Shi Xinmiao;Li Yan;Zhan Siyan;Wang Lin;Wang Zhaoxia;Liu Hui;Ding Jie(Department of Pe diatrics , Peking University First Hospital, Beijing 100034, P. R. China)
出处
《中华医学科研管理杂志》
2018年第4期260-264,共5页
Chinese Journal of Medical Science Research Management
基金
受国家重点研发计划精准医学研究重点专项课题（2016YFC0901505）
儿科遗传性疾病分子诊断与研究北京市重点实验室（BZ0317）
北京市科技计划课题（Z151100003915126）
关键词
大数据
专家共识法
罕见病
调研
Big data
Expert consensus
Rare disease
Survey
