The Danish Lymphoid Cancer Research (DALY-CARE) data resource: the basis for developing data-driven hematology

Christian Brieghel, Mikkel Werling, Casper Møller Frederiksen, Mehdi Parviz, Caspar da Cunha-Bang, Tereza Faitova, Rebecca Svanberg Teglgaard, Noomi Vainer, Thomas Lacoppidan, Emelie Rotbain, Rudi Agius, Carsten Utoft Niemann
{"title":"The Danish Lymphoid Cancer Research (DALY-CARE) data resource: the basis for developing data-driven hematology","authors":"Christian Brieghel, Mikkel Werling, Casper Møller Frederiksen, Mehdi Parviz, Caspar da Cunha-Bang, Tereza Faitova, Rebecca Svanberg Teglgaard, Noomi Vainer, Thomas Lacoppidan, Emelie Rotbain, Rudi Agius, Carsten Utoft Niemann","doi":"10.1101/2024.04.11.24305663","DOIUrl":null,"url":null,"abstract":"Lymphoid-lineage cancers (LC: lymphoma, chronic lymphocytic leukemia, multiple myeloma, and their precursors) share many epidemiological and clinical features. To develop data-driven hematology, we gathered electronic health data and created open-source data processing pipelines to create a comprehensive data resource for Danish LC Research (DALY-CARE) approved for epidemiological, molecular, and data-driven research. We included all Danish adults registered with LC diagnoses since 2002 (n=65,774) and combined 10 nationwide registers, electronic health records (EHR), and laboratory data on a high-powered cloud-computer to develop a secure research environment. We herein exemplify how DALY-CARE has been used to develop novel prognostic markers using biobank data, real-world evidence to evaluate the efficacy of care, and medical artificial intelligence algorithms deployed directly into EHR systems. The DALY-CARE data resource allows for development of both near real-time decision-support tools and extrapolation of clinical trial results to clinical practice, thereby improving care for patients with LC.","PeriodicalId":501203,"journal":{"name":"medRxiv - Hematology","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Hematology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.04.11.24305663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Lymphoid-lineage cancers (LC: lymphoma, chronic lymphocytic leukemia, multiple myeloma, and their precursors) share many epidemiological and clinical features. To develop data-driven hematology, we gathered electronic health data and created open-source data processing pipelines to create a comprehensive data resource for Danish LC Research (DALY-CARE) approved for epidemiological, molecular, and data-driven research. We included all Danish adults registered with LC diagnoses since 2002 (n=65,774) and combined 10 nationwide registers, electronic health records (EHR), and laboratory data on a high-powered cloud-computer to develop a secure research environment. We herein exemplify how DALY-CARE has been used to develop novel prognostic markers using biobank data, real-world evidence to evaluate the efficacy of care, and medical artificial intelligence algorithms deployed directly into EHR systems. The DALY-CARE data resource allows for development of both near real-time decision-support tools and extrapolation of clinical trial results to clinical practice, thereby improving care for patients with LC.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
丹麦淋巴癌研究(DALY-CARE)数据资源:发展数据驱动血液学的基础
淋巴细胞系癌症(LC:淋巴瘤、慢性淋巴细胞白血病、多发性骨髓瘤及其前体)具有许多共同的流行病学和临床特征。为了发展数据驱动的血液学,我们收集了电子健康数据,并创建了开源数据处理管道,为丹麦淋巴细胞系癌症研究(DALY-CARE)创建了一个全面的数据资源,该资源被批准用于流行病学、分子和数据驱动的研究。我们纳入了自 2002 年以来所有登记确诊为慢性淋巴细胞白血病的丹麦成年人(n=65,774),并将 10 个全国性登记簿、电子健康记录 (EHR) 和实验室数据整合到一台高功率云计算机上,以开发一个安全的研究环境。在此,我们将举例说明 DALY-CARE 如何利用生物库数据开发新型预后标记、评估护理效果的真实证据以及直接部署到电子病历系统中的医学人工智能算法。通过 DALY-CARE 数据资源,可以开发近乎实时的决策支持工具,并将临床试验结果推广到临床实践中,从而改善对 LC 患者的护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Machine Learning Insights into HLA Noncoding Sequence Mismatches and Their Impact on DPB1 Matching in Hematopoietic Cell Transplantation Comparison of haemoglobin concentration measurements using HemoCue-301 and Sysmex XN-Series 1500: a survey among anaemic Gambian infants aged 6-12 months Detection of Common Deletion Mutations (− α3.7 and − α4.2 kb) in HBA gene and Genotype-Phenotype Correlation Multi-omic and functional screening reveal targetable vulnerabilities in TP53 mutated multiple myeloma Evaluating the Therapeutic Effects of Amino Acid Treatment on Vaso-Occlusive Pain in Sickle Cell Disease: A Systematic Review and Meta-Analysis Protocol
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1