...
首页> 外文期刊>Statistics in medicine >Statistical methods for building better biomarkers of chronic kidney disease
【24h】

Statistical methods for building better biomarkers of chronic kidney disease

机译:建立慢性肾病更好生物标志物的统计方法

获取原文
获取原文并翻译 | 示例
           

摘要

The last two decades have witnessed an explosion in research focused on the development and assessment of novel biomarkers for improved prognosis of diseases. As a result, best practice standards guiding biomarker research have undergone extensive development. Currently, there is great interest in the promise of biomarkers to enhance research efforts and clinical practice in the setting of chronic kidney disease, acute kidney injury, and glomerular disease. However, some have questioned whether biomarkers currently add value to the clinical practice of nephrology. The current state of the art pertaining to statistical analyses regarding the use of such measures is critical. In December 2014, the National Institute of Diabetes and Digestive and Kidney Diseases convened a meeting, “Toward Building Better Biomarker Statistical Methodology,” with the goals of summarizing the current best practice recommendations and articulating new directions for methodological research. This report summarizes its conclusions and describes areas that need attention. Suggestions are made regarding metrics that should be commonly reported. We outline the methodological issues related to traditional metrics and considerations in prognostic modeling, including discrimination and case mix, calibration, validation, and cost‐benefit analysis. We highlight the approach to improved risk communication and the value of graphical displays. Finally, we address some “new frontiers” in prognostic biomarker research, including the competing risk framework, the use of longitudinal biomarkers, and analyses in distributed research networks.
机译:过去二十年目睹了研究的爆炸,重点是对新型生物标志物的开发和评估进行改善的疾病预后。因此,指导生物标志物研究的最佳实践标准经历了广泛的发展。目前,对生物标志物的承诺非常兴趣,以加强慢性肾病,急性肾损伤和肾小球疾病的环境中的研究努力和临床实践。然而,有些人质疑生物标志物目前是否增加了肾脏临床实践的价值。关于使用这些措施的统计分析的现有技术是至关重要的。 2014年12月,国家糖尿病和消化疾病研究所召开会议,“建立更好的生物标志物统计方法”,以总结当前最佳实践建议和阐明方法研究的新方向的目标。本报告总结了其结论,并描述了需要注意的领域。关于应该普遍报告的指标的建议。我们概述了与传统指标和预后建模中的考虑相关的方法问题,包括歧视和案例混合,校准,验证和成本效益分析。我们突出了提高风险通信和图形显示价值的方法。最后,我们在预后的生物标志物研究中解决了一些“新边界”,包括竞争风险框架,使用纵向生物标志物,以及分布式研究网络的分析。

著录项

  • 来源
    《Statistics in medicine》 |2019年第11期|共1页
  • 作者单位

    Duke Clinical Research Institute Department of Biostatistics and BioinformaticsDuke University;

    Division of Nephrology Department of MedicineJohns Hopkins University School of MedicineBaltimore;

    Division of Kidney Urologic and Hematologic DiseasesNational Institute of Diabetes and Digestive;

    Division of Preventive MedicineBrigham and Women's Hospital Harvard Medical SchoolBoston;

    Departments of Epidemiology Medicine and BiostatisticsJohns Hopkins UniversityBaltimore Maryland;

    Center for Clinical Epidemiology and BiostatisticsPerelman School of Medicine University of;

    Department of Mathematics and StatisticsMount Holyoke CollegeSouth Hadley Massachusetts;

    Center for Clinical Epidemiology and BiostatisticsPerelman School of Medicine University of;

    Division of NephrologyUniversity of California San FranciscoSan Francisco California;

    Division of Nephrology Children's Hospital Los Angeles Department of PediatricsKeck School of;

    Department of Biostatistics School of Public HealthUniversity of MichiganAnn Arbor Michigan;

    Biostatistics ProgramNational Institute of Diabetes and Digestive and Kidney Diseases National;

    Division of Kidney Urologic and Hematologic DiseasesNational Institute of Diabetes and Digestive;

    Division of Kidney Urologic and Hematologic DiseasesNational Institute of Diabetes and Digestive;

    Division of Kidney Urologic and Hematologic DiseasesNational Institute of Diabetes and Digestive;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 卫生调查与统计;
  • 关键词

    calibration; cost‐benefit; discrimination; risk communication; risk model; validation;

    机译:校准;成本效益;歧视;风险沟通;风险模型;验证;

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