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临床生存数据新视角:竞争风险模型

2019-09-25 聂志强, 欧艳秋, 曲艳吉, 袁海云, 刘小清 中华流行病学杂志

临床数据常表现为随访纵向生存资料。由于失访等原因终止时间仍未观察到终点事件,某些研究对象确切的失效时间无法获得,而只知失效事件发生在某特定时间之后的现象称为右删失。右删失数据是临床研究中最常见的生存数据类型,例如患者因术后早期死亡而观察不到远期术后并发症结果,此时若忽略死亡带来的偏倚而直接采用经典Cox分析并发症影响因素是否合理?传统生存分析回归前提是假设删失时间与失效时间独立,即结局不存

临床数据常表现为随访纵向生存资料。由于失访等原因终止时间仍未观察到终点事件,某些研究对象确切的失效时间无法获得,而只知失效事件发生在某特定时间之后的现象称为右删失。右删失数据是临床研究中最常见的生存数据类型,例如患者因术后早期死亡而观察不到远期术后并发症结果,此时若忽略死亡带来的偏倚而直接采用经典Cox分析并发症影响因素是否合理?传统生存分析回归前提是假设删失时间与失效时间独立,即结局不存在竞争风险,该结局是单一终点[1]。临床生存数据常常伴有多个结局,其间可能存在竞争关联关系,此时若使用传统生存分析可能高估累积发生率[2-3]。鉴此,适用于临床右删失数据的竞争风险模型(competing risk model)成为近期临床流行病研究热点[4-6]。本文旨在阐述临床流行病研究中竞争风险的相关概念及其程序的实现。 基本原理 竞争风险是指在观察队列中,存在某种已知事件可能会影响另一种事件发生的概率或者是完全阻碍其发生,则可认为前者与后者存在竞争风险[7]。竞争风险模型适用于多个终点的生存数据[8],关心终点A与不关心终点B非相互独立且存在竞争关系,A发生导致B不会发生,例如慢性肾病患者死亡

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    2019-09-25 CHANGE

    梅斯里提供了很多疾病的模型计算公式,赞一个!

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