Optimal use of prognostic factors in non-Hodgkin lymphoma.
Optimal use of prognostic factors in non-Hodgkin lymphoma.
复制标题
非霍奇金淋巴瘤预后因素的最佳利用。
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
L. Sehn
中科院分区：
文献类型：
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作者：
L. Sehn
非霍奇金淋巴瘤的管理是复杂的广泛异质性内公认的亚型。具有假定相似诊断的患者可以具有显著不同的临床表现、分子特征和临床结果。可靠的预后标志物可以识别可能从替代方法中受益的患者子集。历史上，已经阐明了大量的临床和分子预后因素。然而，最近引入的新疗法，如单克隆抗体，彻底改变了治疗实践，大大改善了结果。这让人们对之前公认的预后因素的价值产生了质疑，这些因素需要在免疫化疗时代重新验证。似乎常用的临床指标（IPI和FLIPI）保留了预测能力，尽管它们识别非常差的结局组的能力有限。目前还没有分子标志物已被重新验证，并显示在弥漫性大B细胞淋巴瘤或滤泡性淋巴瘤的当前治疗实践的设置中保留意义。分子研究提供的生物学见解应该允许开发更多的靶向治疗，这将增加治疗选择和未来定制治疗的可能性。今后必须在精心设计的临床试验的背景下，对临床和生物标志物进行前瞻性相关研究。这将使我们能够在治疗变化的背景下持续评估结果预测因子，并合理设计定制的治疗算法。
The management of non-Hodgkin lymphoma is complicated by wide heterogeneity within recognized subtypes. Patients with supposedly similar diagnoses can have remarkably varied clinical presentations, molecular profiles and clinical outcomes. Reliable prognostic markers could allow the identification of patient subsets that may benefit from alternate approaches. Historically, a large number of clinical and molecular prognostic factors have been elucidated. However, the recent introduction of new therapies such as monoclonal antibodies has revolutionized treatment practices and greatly improved outcomes. This has called into question the value of previously recognized prognostic factors that need to be revalidated in the era of immunochemotherapy. It would appear that the commonly used clinical indices (IPI and FLIPI) retain predictive capacity, although they may have limited ability to identify a very poor outcome group. Currently there are no molecular markers that have been revalidated and shown to retain significance in the setting of current treatment practices for diffuse large B-cell lymphoma or follicular lymphoma. The biologic insights provided by molecular studies should allow for more targeted therapies to be developed, which will increase treatment choice and the possibility of tailored therapy in the future. It is imperative that future steps forward be made in the context of well-designed clinical trials with prospective correlative studies of clinical and biologic markers. This will allow us to continuously assess outcome predictors in the context of treatment change and to rationally design tailored treatment algorithms.
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