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在死亡率流行病学研究中,限制向社会保障管理局死亡主文件匹配系统提交数据对国家死亡指数确定的影响。

The impact on National Death Index ascertainment of limiting submissions to Social Security Administration Death Master File matches in epidemiologic studies of mortality.

作者信息

Hermansen Sigurd W, Leitzmann Michael F, Schatzkin Arthur

机构信息

Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Blvd., Rockville, MD 20852, USA.

出版信息

Am J Epidemiol. 2009 Apr 1;169(7):901-8. doi: 10.1093/aje/kwn404. Epub 2009 Feb 27.

Abstract

Although many epidemiologists use the National Death Index (NDI) as the "gold standard" for ascertainment of US mortality, high search costs per year and per subject for large cohorts warrant consideration of less costly alternatives. In this study, for 1995-2001 deaths, the authors compared matches of a random sample of 11,968 National Institutes of Health (NIH)-AARP Diet and Health Study subjects to the Social Security Administration's Death Master File (DMF) and commercial list updates (CLU) with matches of those subjects to the NDI. They examined how varying the lower limits of estimated DMF match probabilities (m scores of 0.60, 0.20, and 0.05) altered the benefits and costs of mortality ascertainment. Observed DMF/CLU ascertainment of NDI-identified decedents increased from 89.8% to 95.1% as m decreased from 0.60 (stringent) to 0.20 (less stringent) and increased further to 96.4% as m decreased to 0.05 (least stringent). At these same cutpoints, the false-match probability increased from 0.4% of the sample to 0.6% and then 2.3%. Limiting NDI cause-of-death searches to subjects found in DMF searches using less stringent match criteria, further supplemented by CLU vital status updates, improves vital status assessment while increasing substantially the cost-effectiveness of ascertaining mortality in large prospective cohort studies.

摘要

尽管许多流行病学家将国家死亡指数(NDI)用作确定美国死亡率的“金标准”,但对于大型队列而言,每年和每个研究对象的高昂搜索成本促使人们考虑成本较低的替代方法。在本研究中,针对1995 - 2001年的死亡情况,作者将11968名美国国立卫生研究院(NIH)-美国退休人员协会饮食与健康研究对象的随机样本与社会保障管理局的死亡主文件(DMF)及商业名单更新(CLU)的匹配情况,与这些对象与NDI的匹配情况进行了比较。他们研究了改变估计的DMF匹配概率下限(m分数为0.60、0.20和0.05)如何改变死亡率确定的收益和成本。随着m从0.60(严格)降至0.20(不太严格),观察到的由DMF/CLU确定的NDI识别出的死者比例从89.8%增至95.1%,当m降至0.05(最不严格)时进一步增至96.4%。在这些相同的切点上,假匹配概率从样本的0.4%增至0.6%,然后增至2.3%。在大型前瞻性队列研究中,使用不太严格的匹配标准将NDI死因搜索限制在DMF搜索中找到的对象,并进一步由CLU生命状态更新进行补充,可改善生命状态评估,同时大幅提高确定死亡率的成本效益。

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