Specification of Estimands for Complex Disease Processes Using Multistate Models and Utility Functions

利用多状态模型和效用函数对复杂疾病过程的估计量进行规范

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Abstract

In complex diseases, individuals are often at risk of several types of possibly semi-competing events and may experience recurrent symptomatic episodes. This complex disease course makes it challenging to define target estimands for clinical trials. While composite endpoints are routinely adopted, recent innovations involving the win ratio and other methods based on ranking the disease course have received considerable attention. We emphasize the usefulness of multistate models for addressing challenges arising in complex diseases, along with the simplicity and interpretability that come from defining utilities to synthesize evidence of treatment effects on different aspects of the disease process. Robust variance estimation based on the infinitesimal jackknife means that such methods can be used as the basis of primary analyses of clinical trials. We illustrate the use of utilities for the assessment of bleeding outcomes in a trial of cancer patients with thrombocytopenia.

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