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

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
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引用次数: 0

摘要

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