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A Proposed Method to Adjust for Selection Bias in Cohort Studies

机译:队列研究中选择偏倚的调整方法

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摘要

Selection bias is a concern in cohort studies in which selection into the cohort is related to the studied outcome.nAn example is chronic infection with hepatitis C virus, where the initial infection may be asymptomatic for decades.nThis problem leads to selection of more severely ill individuals into registers of such infections. Cohort studies oftennadjust for this bias by introducing a time window between entry into the cohort and entry into the study. This paperndescribes and assesses a novel method to improve adjustment for this type of selection bias. The size of the timenwindow is decided by calculating a standardized incidence ratio as a continuous function of the size of the timenwindow. The resulting graph is used to decide on an appropriate window size. The method is evaluated by usingnthe Swedish register of hepatitis C virus infections for 1990–2006. The complications studied were non-Hodgkinnlymphoma and liver cancer. Selection bias differed for the studied outcomes, and a time window of a minimum ofn2 months and 12 months, respectively, was judged to be appropriate. The novel method may have advantagesncompared with an interval-based method, especially in cohort studies with small numbers of events.
机译:在队列研究中,选择偏倚是一个令人关注的问题,在队列研究中,选择与研究结果有关。n例如,慢性丙型肝炎病毒感染,最初的感染可能数十年无症状.n这个问题导致选择重症患者个人进入此类感染的记录。队列研究通常通过在进入队列与进入研究之间引入时间窗口来适应这种偏见。本文描述并评估了一种新颖的方法来改进对这种选择偏差的调整。通过将标准化的发生率计算为时间窗口的大小的连续函数来确定时间窗口的大小。结果图用于确定适当的窗口大小。该方法通过瑞典1990-2006年丙型肝炎病毒感染登记簿进行评估。研究的并发症是非霍奇金淋巴瘤和肝癌。选择的偏倚因所研究的结果而异,并且分别以至少2个月和12个月的时间窗为宜。与基于间隔的方法相比,该新方法可能具有优势,尤其是在事件数量较少的队列研究中。

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