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首页> 外文期刊>Journal of Clinical Epidemiology >Cohort studies were found to be frequently biased by missing disease information due to death
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Cohort studies were found to be frequently biased by missing disease information due to death

机译:发现队列研究经常因死亡而经常被缺失的疾病信息偏见

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ObjectivesIn epidemiologic cohort studies with missing disease information due to death (MDID), conventional analyses right-censoring death cases at the last observation or at death may yield significant bias in relative risk and hazard ratio estimates. The aim of this study was to investigate susceptibility to this bias and assess its potential direction and magnitude. Study Design and SettingLiterature review of selected epidemiologic, geriatric, and environmental journals in 2011–2012 and simulation study of various conventional approaches to handling missing disease data. A study was considered susceptible to MDID bias if disease information was collected at follow-up visits only, and a conventional analysis was performed on the data. ResultsOf 125 identified studies, 58 (46.4%, 95% confidence interval [CI]: 37.7–55.1%) were classified as susceptible to MDID bias, of which six (10.3%, 95% CI: 2.5–18.2%) attempted to address this in sensitivity analyses. The simulation revealed that depending on the analytic strategy for handling missing disease data, the potential exists for significant under- or over-estimation of risk factor effect estimates. ConclusionAwareness of MDID bias is important as more adequate analysis methods exist permitting an unbiased analysis. Recommendations for better reporting and analysis of MDID are provided.
机译:目的流行病学队列研究与死亡(Mdid)引起的缺失的疾病信息,常规分析最后一次观察或死亡的右审查死亡病例可能会产生相对风险和危险比估算的显着偏差。本研究的目的是调查对这种偏差的敏感性,并评估其潜在的方向和幅度。 2011 - 2011年选定流行病学,老年节和环境期刊的研究设计与环境综述,以及处理缺失疾病数据的各种常规方法的仿真研究。如果仅在随访访问时收集疾病信息,则认为易受MDID偏差的研究,并且对数据进行常规分析。结果125鉴定研究,58例(46.4%,95%置信区间[CI]:37.7-55.1%)被归类为易受Mdid偏差的影响,其中六(10.3%,95%CI:2.5-18.2%)试图解决这在敏感性分析中。模拟显示,根据用于处理缺失的疾病数据的分析策略,存在危险因素效应估计的显着估计或过度估计的潜力。结论MDID偏差的特征是重要的,因为允许无偏见的分析存在更具足够的分析方法。提供了更好地报告和分析MDID的建议。

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