Data-driven desirability function to measure patients' disease progression in a longitudinal study

Chen Hsiu-Wen; Wong Weng Kee; Xu Hongquan

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Data-driven desirability function to measure patients' disease progression in a longitudinal study

机译：在纵向研究中，数据驱动的期望功能可测量患者的疾病进展

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摘要

Multiple outcomes are increasingly used to assess chronic disease progression. We discuss and show how desirability functions can be used to assess a patient overall response to a treatment using multiple outcome measures and each of them may contribute unequally to the final assessment. Because judgments on disease progression and the relative contribution of each outcome can be subjective, we propose a data-driven approach to minimize the biases by using desirability functions with estimated shapes and weights based on a given gold standard. Our method provides each patient with a meaningful overall progression score that facilitates comparison and clinical interpretation. We also extend the methodology in a novel way to monitor patients' disease progression when there are multiple time points and illustrate our method using a longitudinal data set from a randomized two-arm clinical trial for scleroderma patients.

机译：越来越多的结果被用于评估慢性疾病的进展。我们讨论并显示了可取性函数如何用于使用多个结果度量来评估患者对治疗的总体反应，并且它们中的每一个都可能对最终评估产生不平等的影响。由于对疾病进展和每种结果的相对贡献的判断可能是主观的，因此我们提出了一种数据驱动的方法，以基于给定金标准的期望形状和权重使用期望函数，以将偏差最小化。我们的方法为每位患者提供了有意义的总体进展评分，有助于进行比较和临床解释。我们还以一种新颖的方式扩展了该方法，以在存在多个时间点时监测患者的疾病进展，并使用来自硬皮病患者的随机两臂临床试验的纵向数据集说明了我们的方法。

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来源
《Journal of applied statistics》 |2016年第8期|783-795|共13页
作者
Chen Hsiu-Wen; Wong Weng Kee; Xu Hongquan;
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作者单位

Chung Yuan Christian Univ, Dept Ind & Syst Engn, Taoyuan 32023, Taiwan;

Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA 90095 USA;

Univ Calif Los Angeles, Dept Stat, Los Angeles, CA 90095 USA;

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正文语种 eng
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关键词
longitudinal data; multiple outcomes; scleroderma; desirability function; nonlinear least squares;

机译：纵向数据;多结果;硬皮病;期望函数;非线性最小二乘;

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Data-driven desirability function to measure patients' disease progression in a longitudinal study

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