利用多源数据为霍奇金淋巴瘤患者提供个性化治疗

IF 6.9 2区 医学 Q1 HEMATOLOGY
Susan K. Parsons , Angie Mae Rodday , Jenica N. Upshaw , Carlton D. Scharman , Zhu Cui , Yenong Cao , Yun Kyoung Ryu Tiger , Matthew J. Maurer , Andrew M. Evens
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引用次数: 0

摘要

霍奇金淋巴瘤是一种罕见的癌症,但治愈率很高,主要困扰青少年和年轻人。尽管在过去二十年中进行了多项开创性试验,但除了使用多机构化疗进行根治外,目前还没有一种基于共识的治疗方法。放射治疗作为综合治疗方式的一部分,以及作为一种重要的巩固治疗方式,在早期疾病中的应用仍存在争议。在过去十年中,新型疗法已被用于自体干细胞移植前的准备和移植后的巩固治疗。最近,这些新型疗法已进入一线治疗,最初是与标准治疗进行比较,后来是与多药化疗进行直接正面比较。2018年,我们成立了HoLISTIC联盟,汇集疾病和方法专家,根据患者个体数据开发临床决策模型,为医疗服务提供者、患者和护理人员提供决策指导。在这篇综述中,我们详细介绍了利用数据科学原理创建过去 20 年接受治疗的患者个体数据主数据库的步骤。然后,我们介绍了临床决策所采用的不同方法,从诊断时的临床预测工具到多状态模型,再到治疗及其反应。最后,我们介绍了如何根据前线治疗和挽救治疗的累积暴露情况,利用模拟建模来估算晚期效应的风险。由此产生的数据库和所使用的工具是动态的,有望随着更好、更完整的信息的出现而不断更新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harnessing multi-source data for individualized care in Hodgkin Lymphoma

Hodgkin lymphoma is a rare, but highly curative form of cancer, primarily afflicting adolescents and young adults. Despite multiple seminal trials over the past twenty years, there is no single consensus-based treatment approach beyond use of multi-agency chemotherapy with curative intent. The use of radiation continues to be debated in early-stage disease, as part of combined modality treatment, as well as in salvage, as an important form of consolidation. While short-term disease outcomes have varied little across these different approaches across both early and advanced stage disease, the potential risk of severe, longer-term risk has varied considerably.

Over the past decade novel therapeutics have been employed in the retrieval setting in preparation to and as consolidation after autologous stem cell transplant. More recently, these novel therapeutics have moved to the frontline setting, initially compared to standard-of-care treatment and later in a direct head-to-head comparison combined with multi-agent chemotherapy.

In 2018, we established the HoLISTIC Consortium, bringing together disease and methods experts to develop clinical decision models based on individual patient data to guide providers, patients, and caregivers in decision-making. In this review, we detail the steps we followed to create the master database of individual patient data from patients treated over the past 20 years, using principles of data science. We then describe different methodological approaches we are taking to clinical decision making, beginning with clinical prediction tools at the time of diagnosis, to multi-state models, incorporating treatments and their response. Finally, we describe how simulation modeling can be used to estimate risks of late effects, based on cumulative exposure from frontline and salvage treatment.

The resultant database and tools employed are dynamic with the expectation that they will be updated as better and more complete information becomes available.

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来源期刊
Blood Reviews
Blood Reviews 医学-血液学
CiteScore
13.80
自引率
1.40%
发文量
78
期刊介绍: Blood Reviews, a highly regarded international journal, serves as a vital information hub, offering comprehensive evaluations of clinical practices and research insights from esteemed experts. Specially commissioned, peer-reviewed articles authored by leading researchers and practitioners ensure extensive global coverage across all sub-specialties of hematology.
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