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一种使用CVX寻找精准医学最优交叉设计的有效方法。

An Efficient Way to Find Optimal Crossover Designs Using CVX for Precision Medicine.

作者信息

Li Yin, Wong Weng Kee, Zhou Hua, Carriere Keumhee Chough

机构信息

Ontario Medical Association.

University of California-Los Angeles.

出版信息

J Data Sci Stat Vis. 2024 Apr;4(3). doi: 10.52933/jdssv.v4i3.83. Epub 2024 Jun 4.

Abstract

Crossover designs play an increasingly important role in precision medicine. We formulate the optimal crossover design problem as a convex optimization problem and demonstrate that the convex optimization package CVX is effective for searching a broad class of optimal crossover designs, including cases where analytical optimal crossover designs are unavailable. We also use CVX to search for N-of-1 trials frequently used in precision medicine and dual-objective optimal crossover designs to estimate treatment effects and carryover treatment effects with unequal interest. We provide CVX codes and as illustrations, use them to find optimal crossover designs under the A-optimality criterion.

摘要

交叉设计在精准医学中发挥着越来越重要的作用。我们将最优交叉设计问题表述为一个凸优化问题,并证明凸优化软件包CVX对于搜索广泛类别的最优交叉设计是有效的,包括那些无法获得解析最优交叉设计的情况。我们还使用CVX来搜索精准医学中常用的单病例试验以及双目标最优交叉设计,以估计治疗效果和具有不等关注度的残留治疗效果。我们提供了CVX代码,并作为示例,使用它们来找到在A-最优性准则下的最优交叉设计。

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