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荟萃分析 Cox 比例风险模型×个体患者数据荟萃分析×
领域流行病学证据综合
方法族Process / pipelineProcess / pipeline
起源年份1998–20071990s
提出者Parmar, Torri & Stewart; Tierney et al.Cochrane Collaboration, Pioneered by Stewart & Clarke
类型Meta-analytic survival modelMethod
开创性文献Tierney, J. F., Stewart, L. A., Ghersi, D., Burdett, S., & Sydes, M. R. (2007). Practical methods for incorporating summary time-to-event data into meta-analysis. Trials, 8(1), 16. DOI ↗Stewart, L. A., Clarke, M. J., & Cochrane IPD Meta-analysis Methods Group. (2015). Practical methodology of meta-analyses (including IPD) of randomised trials reporting time to event data. Cochrane Database of Systematic Reviews, 2015(10), MR000027. link ↗
别名pooled Cox regression meta-analysis, meta-Cox model, survival meta-analysis, Cox PH poolingIPD Meta-Analysis, Participant-Level Data Synthesis, One-Stage Meta-Analysis
相关31
摘要Meta-analytic Cox proportional hazards is a quantitative synthesis technique that pools log hazard ratios from multiple Cox regression survival analyses into a single, more precise estimate of the association between an exposure or treatment and a time-to-event outcome. It combines the inferential power of survival analysis with the evidence-aggregation logic of meta-analysis, making it the standard approach for summarising multi-study survival evidence in clinical and epidemiological research.Individual patient data meta-analysis (IPD-MA) is a systematic synthesis method where researchers obtain and analyze raw data at the patient level from multiple randomized controlled trials, rather than relying on published summary statistics (aggregate data). Pioneered by the Cochrane Collaboration and formalized by Stewart, Clarke, and Riley, IPD-MA is considered the gold standard for evidence synthesis because it enables consistent outcome definition across trials, robust subgroup analysis, and detection of treatment-covariate interactions. Though time-intensive and resource-demanding, IPD-MA provides the most reliable estimates of intervention effects and is preferred for critical clinical decisions, particularly for identifying which patients benefit most from treatment.
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ScholarGate方法对比: Meta-analytic Cox proportional hazards · Individual Patient Data Meta-Analysis. 于 2026-06-20 检索自 https://scholargate.app/zh/compare