Meta-Analysis of Clinical Trials With Sparse Binary Outcomes Using Zero-Inflated Binomial (ZIB) Models

被引:6
作者
Dong, Cheng [1 ]
Zhao, Yueqin [2 ]
Tiwari, Ram [3 ]
机构
[1] Univ Missouri, Dept Stat, Columbia, MO 65211 USA
[2] US FDA, Div Biometr 7, Off Biostat, OTS,CDER, Silver Spring, MD 20993 USA
[3] US FDA, Div Biostat, OSB, CDRH, Silver Spring, MD USA
来源
STATISTICS IN BIOPHARMACEUTICAL RESEARCH | 2019年 / 11卷 / 03期
关键词
EM algorithm; Fixed-effects model; Rare events; 2; X-2; TABLES; MYOCARDIAL-INFARCTION; ROSIGLITAZONE; REGRESSION; POISSON; RISK;
D O I
10.1080/19466315.2018.1537885
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In meta-analysis of clinical trials, standard statistical methods run into problems when the proportions of safety events are small. Motivated by the dataset used in a published analysis of cardiovascular safety in Rosiglitazone trials, this article proposes using a zero-inflated binomial model to handle the zero-event trials. The maximum likelihood estimates of the model parameters are obtained using the expectation and maximization algorithm. Via simulation studies, it is shown that the proposed methods provide estimates of odds ratios with less bias and variation, compared with both the Mantel-Hanszel method with continuity correction and Peto's method. The proposed methods are applied to the Rosiglitazone trials. for this article are available online.
引用
收藏
页码:228 / 238
页数:11
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