Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomes
Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomes
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DOI：
10.1002/bimj.200290004
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发表时间：
2002-01-01
影响因子：
1.7
通讯作者：
Buyse, M
中科院分区：
文献类型：
--
作者：
Renard, D;Geys, H;Buyse, M
本文将BUYSE等人（2000）在元分析设置中验证代理端点的工作扩展到两个离散结果的情况下，重点是二元端点。该方法需要拟合代理和真端点的联合模型，其中包括几个随机效应。我们建议使用成对似然（PL）方法来拟合这个模型，这种方法似乎比最大似然或惩罚似然更适合手头的问题。PL估计器的性能在有限模拟的基础上进行了评估，该方法的数据来自五项比较抗精神病药物治疗慢性精神分裂症的临床试验的荟萃分析。
This article extends the work of BUYSE et al. (2000) on the validation of surrogate endpoints in a meta-analytic setting to the case of two discrete outcomes, the focus being on binary endpoints. The methodology entails fitting of a joint model for the surrogate and the true endpoints that includes several random effects. We propose to fit this model using a pairwise likelihood (PL) approach which seems better suited to the problem at hand than maximum likelihood or penalized quasi-likelihood. The performance of the PL estimator is evaluated on the grounds of limited simulations and the methodology is illustrated on data from a meta-analysis of five clinical trials comparing antipsychotic agents for the treatment of chronic schizophrenia.