• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of the royal statistical society >Temporal trends of biomarkers and between-biomarker associations
【24h】

Temporal trends of biomarkers and between-biomarker associations

机译：生物标志物和生物标志物间关联的时间趋势

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We are interested in the temporal trends of biomarkers that are related to disease progression, especially the association between two temporal trends. When biological mechanisms are lacking, no parametric forms of the temporal trends are theoretically justified. In this work, we adopt joint non-parametric local linear mixed effects modelling. By local linear regression, each temporal trend is represented by its magnitude and slope (the primary interest in medical studies) which both change with time. By mixed effects modelling, we take care of data sparsity within each subject and the large subject-to-subject variability. The association between two temporal trends is evaluated by the correlation coefficient matrix, assessing association in terms of both the magnitude and the slope. The joint modelling enables evaluation of the association as a continuous function of time, even if one or neither biomarker is observed at some specific time points. We apply the method proposed to a study of human immunodeficiency virus patients following anti-retroviral therapy until viral suppression. We find that associations between some biomarkers change over time, reflecting potentially changing stages of disease.
机译：我们对与疾病进展相关的生物标志物的时间趋势感兴趣，尤其是两个时间趋势之间的关联。当缺乏生物学机制时，理论上没有理由证明时间趋势的参数形式。在这项工作中，我们采用联合非参数局部线性混合效应建模。通过局部线性回归，每个时间趋势都由其幅度和斜率（医学研究中的主要兴趣）表示，它们都随时间变化。通过混合效果建模，我们可以处理每个主题内的数据稀疏性以及较大的主题间差异。通过相关系数矩阵评估两个时间趋势之间的关联，并根据幅度和斜率评估关联。即使在某些特定时间点未观察到一个或两个生物标记，联合建模也可以将关联作为时间的连续函数进行评估。我们将提出的方法用于抗逆转录病毒治疗直至病毒抑制的人类免疫缺陷病毒患者的研究。我们发现某些生物标志物之间的关联会随着时间而变化，反映出疾病潜在的变化阶段。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号