Heudel Pierre, Crochet Hugo, Durand Thierry, Zrounba Philippe, Blay Jean-Yves
Department of Medical Oncology, Centre Léon Bérard, Lyon, France.
Data and Artificial Intelligence Team, Centre Léon Bérard, Lyon, France.
PLOS Digit Health. 2023 Dec 19;2(12):e0000415. doi: 10.1371/journal.pdig.0000415. eCollection 2023 Dec.
In a comprehensive cancer center, effective data strategies are essential to evaluate practices, and outcome, understanding the disease and prognostic factors, identifying disparities in cancer care, and overall developing better treatments. To achieve these goals, the Center Léon Bérard (CLB) considers various data collection strategies, including electronic medical records (EMRs), clinical trial data, and research projects. Advanced data analysis techniques like natural language processing (NLP) can be used to extract and categorize information from these sources to provide a more complete description of patient data. Data sharing is also crucial for collaboration across comprehensive cancer centers, but it must be done securely and in compliance with regulations like GDPR. To ensure data is shared appropriately, CLB should develop clear data sharing policies and share data in a controlled, standardized format like OSIRIS RWD, OMOP and FHIR. The UNICANCER initiative has launched the CONSORE project to support the development of a structured and standardized repository of patient data to improve cancer research and patient outcomes. Real-world data (RWD) studies are vital in cancer research as they provide a comprehensive and accurate picture of patient outcomes and treatment patterns. By incorporating RWD into data collection, analysis, and sharing strategies, comprehensive cancer centers can take a more comprehensive and patient-centered approach to cancer research. In conclusion, comprehensive cancer centers must take an integrated approach to data collection, analysis, and sharing to enhance their understanding of cancer and improve patient outcomes. Leveraging advanced data analytics techniques and developing effective data sharing policies can help cancer centers effectively harness the power of data to drive progress in cancer research.
在综合性癌症中心,有效的数据策略对于评估医疗实践及结果、了解疾病和预后因素、识别癌症治疗中的差异以及总体上开发更好的治疗方法至关重要。为实现这些目标,莱昂·贝拉尔中心(CLB)考虑了各种数据收集策略,包括电子病历(EMR)、临床试验数据和研究项目。像自然语言处理(NLP)这样的先进数据分析技术可用于从这些来源提取和分类信息,以提供更完整的患者数据描述。数据共享对于综合性癌症中心之间的合作也至关重要,但必须安全地进行,并符合《通用数据保护条例》(GDPR)等法规。为确保数据得到适当共享,CLB应制定明确的数据共享政策,并以诸如OSIRIS真实世界数据、观测医疗效果合作组织(OMOP)和快速医疗互操作性资源(FHIR)等受控的标准化格式共享数据。UNICANCER倡议已启动CONSORE项目,以支持开发结构化和标准化的患者数据存储库,以改善癌症研究和患者预后。真实世界数据(RWD)研究在癌症研究中至关重要,因为它们提供了患者预后和治疗模式的全面而准确的情况。通过将真实世界数据纳入数据收集、分析和共享策略,综合性癌症中心可以采取更全面、以患者为中心的癌症研究方法。总之,综合性癌症中心必须采取综合方法进行数据收集、分析和共享,以增强对癌症的理解并改善患者预后。利用先进的数据分析技术和制定有效的数据共享政策有助于癌症中心有效地利用数据的力量,推动癌症研究取得进展。