Estimating Correlations Between Clinical Trial Outcomes Using Generalised Estimating Equations
提出一种基于广义估计方程的新算法，用于估计大型临床试验数据集中的结果相关性，发现同一治疗领域内试验的相关性约为10%，相同阶段或机制层次的相关性高达40%，而针对同一疾病的试验呈轻微负相关。
ABSTRACT Accurately estimating the correlations among clinical trial outcomes is crucial for managing the risk of biopharmaceutical investment portfolios. We propose a novel algorithm for estimating correlations in large clinical trial datasets using a generalised estimating equations (GEE) framework. Our algorithm outperforms existing methods in both convergence speed and computational efficiency. Empirical analysis of over 25,000 clinical trials reveals a correlation of approximately 10% for trials within therapeutic areas and up to 40% for trials sharing the same phase or mechanism hierarchy. Trials targeting the same disease show slightly negative correlations, suggesting a first‐mover advantage. Our approach offers a scalable method to estimate correlations within large clinical trial datasets.