Phillips Charles A, Pollock Brad H
Division of Oncology, Children's Hospital of Philadelphia, Philadelphia, PA.
Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
J Natl Cancer Inst Monogr. 2019 Sep 1;2019(54):127-131. doi: 10.1093/jncimonographs/lgz019.
Recognition and treatment of malnutrition in pediatric oncology patients is crucial because it is associated with increased morbidity and mortality. Nutrition-relevant data collected from cancer clinical trials and nutrition-specific studies are insufficient to drive high-impact nutrition research without augmentation from additional data sources. To date, clinical big data resources are underused for nutrition research in pediatric oncology. Health-care big data can be broadly subclassified into three clinical data categories: administrative, electronic health record (including clinical data research networks and learning health systems), and mobile health. Along with -omics data, each has unique applications and limitations. We summarize the potential use of clinical big data to drive pediatric oncology nutrition research and identify key scientific gaps. A framework for advancement of big data utilization for pediatric oncology nutrition research is presented and focuses on transdisciplinary teams, data interoperability, validated cohort curation, data repurposing, and mobile health applications.
识别和治疗儿科肿瘤患者的营养不良至关重要，因为这与发病率和死亡率的增加有关。从癌症临床试验和营养专项研究中收集的营养相关数据不足以推动具有重大影响的营养研究，而无需其他数据源的补充。迄今为止，临床大数据资源在儿科肿瘤学营养研究中未得到充分利用。医疗保健大数据可大致细分为三类临床数据：管理数据、电子健康记录（包括临床数据研究网络和学习健康系统）以及移动健康数据。与组学数据一样，每类数据都有独特的应用和局限性。我们总结了临床大数据在推动儿科肿瘤学营养研究方面的潜在用途，并确定了关键的科学差距。本文提出了一个推进儿科肿瘤学营养研究大数据利用的框架，该框架侧重于跨学科团队、数据互操作性、经过验证的队列管理、数据再利用以及移动健康应用。
