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在 CLL 中使用预后模型实现临床护理的个体化:我们做到了吗?

Using prognostic models in CLL to personalize approach to clinical care: Are we there yet?

机构信息

Dept. of Internal Medicine, Kansas University Medical Ctr, Kansas City, KS, USA.

Dept. of Malignant Hematology, Moffitt Cancer Ctr, Tampa, FL, USA.

出版信息

Blood Rev. 2018 Mar;32(2):159-166. doi: 10.1016/j.blre.2017.10.003. Epub 2017 Oct 28.

Abstract

Four decades ago, two staging systems were developed to help stratify CLL into different prognostic categories. These systems, the Rai and the Binet staging, depended entirely on abnormal exam findings and evidence of anemia and thrombocytopenia. Better understanding of biologic, genetic, and molecular characteristics of CLL have contributed to better appreciating its clinical heterogeneity. New prognostic models, the GCLLSG prognostic index and the CLL-IPI, emerged. They incorporate biologic and genetic information related to CLL and are capable of predicting survival outcomes and cases anticipated to need therapy earlier in the disease course. Accordingly, these newer models are helping develop better informed surveillance strategies and ultimately tailor treatment intensity according to presence (or lack thereof) of certain prognostic markers. This represents a step towards personalizing care of CLL patients. We anticipate that as more prognostic factors continue to be identified, the GCLLSG prognostic index and CLL-IPI models will undergo further revisions.

摘要

四十年前,两种分期系统被开发出来,用于帮助将 CLL 分为不同的预后类别。这些系统,即 Rai 和 Binet 分期,完全依赖于异常的检查结果以及贫血和血小板减少的证据。对 CLL 的生物学、遗传学和分子特征的更好理解有助于更好地理解其临床异质性。新的预后模型,即 GCLLSG 预后指数和 CLL-IPI,已经出现。它们包含与 CLL 相关的生物学和遗传学信息,能够预测生存结果和预计在疾病过程中更早需要治疗的病例。因此,这些新模型有助于制定更好的监测策略,并根据存在(或不存在)某些预后标志物来调整治疗强度。这代表着朝着为 CLL 患者提供个性化护理迈出了一步。我们预计,随着更多的预后因素被不断发现,GCLLSG 预后指数和 CLL-IPI 模型将进行进一步修订。

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