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多次生存数据荟萃分析的迭代广义最小二乘法

Iterative generalized least squares for meta-analysis of survival data at multiple times.

作者信息

Dear K B

机构信息

Technology Assessment Group, Harvard School of Public Health, Boston, Massachusetts 02115.

出版信息

Biometrics. 1994 Dec;50(4):989-1002.

PMID:7787011
Abstract

A method is presented for joint analysis of survival proportions reported at multiple times in published studies to be combined in a meta-analysis. Generalized least squares is used to fit linear models including between-trial and within-trial covariates, using current fitted values iteratively to derive correlations between times within studies. Multi-arm studies and nonrandomized historical controls can be included with no special handling. The method is illustrated with data from two previously published meta-analyses. In one, an early treatment difference is detected that was not apparent in the original analysis.

摘要

本文提出了一种方法,用于对已发表研究中多次报告的生存比例进行联合分析,以便在荟萃分析中进行合并。使用广义最小二乘法拟合线性模型,该模型包括试验间和试验内协变量,并使用当前拟合值进行迭代,以得出研究内不同时间点之间的相关性。多臂研究和非随机历史对照无需特殊处理即可纳入。通过两项先前发表的荟萃分析中的数据对该方法进行了说明。在其中一项分析中,检测到了一个早期治疗差异,该差异在原始分析中并不明显。

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