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腺癌的靶向治疗的临床荟萃分析。

Clinical meta-analyses of targeted therapies in adenocarcinoma.

机构信息

Medical Oncology, Azienda Ospedaliera Universitaria Integrata (A.O.U.I.), University of Verona, Verona, Italy.

出版信息

Target Oncol. 2013 Mar;8(1):35-45. doi: 10.1007/s11523-013-0262-0. Epub 2013 Jan 25.

Abstract

Although the interpretation of the data reported in meta-analyses may hide several issues, it is undoubtable that this methodological approach may significantly contribute to implement the results of clinical trials, and represent a useful and practical tool for the evidence-based medicine process. Indeed, level-one recommendations should consider well-conducted meta-analyses as well as large and adequately powered randomized trials as the main contributors for the definition of guidelines for clinical practice. In addition, the role of meta-analyses for issues whereas conflicting data (and/or unpowered results) are provided, is well established. In the field of lung cancer, meta-analyses already participated to change the current standard, and are now facing the challenging issues of predictive biomarkers of prognosis and/or efficacy of targeted agents. With this aim, the meta-analytic approach helped in the recent years to implement the quantification of the magnitude of the benefit of targeted agents, and added new insights by interpreting the data coming from clinical trials by integrating them with biomarkers. The treatment-interaction analyses according to putative predictive factors of efficacy may clarify unknown issues and generate new hypotheses for future perspectives. The current review attempts to put in the context of the clinical data of targeted agents for lung cancer all the pros and cons of the meta-analytic process published to date, and critically analyze all the potential perspectives which this methodology may add for both current practice and forthcoming research.

摘要

尽管荟萃分析报告的数据解释可能隐藏了一些问题,但不可否认的是,这种方法学方法可能会极大地促进临床试验结果的实施,并为循证医学过程提供有用且实用的工具。实际上,一级推荐应该将精心设计的荟萃分析以及大型和充分有力的随机试验视为制定临床实践指南的主要贡献因素。此外,荟萃分析在提供相互矛盾的数据(和/或无能力结果)的问题上的作用已经得到充分证实。在肺癌领域,荟萃分析已经参与改变了当前的标准,现在正面临着预后和/或靶向药物疗效预测生物标志物的挑战性问题。为此,荟萃分析方法有助于近年来量化靶向药物的获益程度,并通过将临床试验数据与生物标志物相结合来解释数据,从而提供新的见解。根据可能的疗效预测因素进行的治疗相互作用分析可以澄清未知问题,并为未来的研究提供新的假设。本综述试图将迄今为止发表的有关肺癌靶向药物的荟萃分析结果的临床数据置于背景之下,并批判性地分析这种方法可能为当前实践和即将到来的研究带来的所有潜在视角。

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