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Chin J Cancer. 2013 May;32(5):233-41. doi: 10.5732/cjc.012.10248. Epub 2013 Mar 15.
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本文引用的文献

1
Evaluation of early efficacy endpoints for proof-of-concept trials.概念验证试验早期疗效终点的评估。
J Biopharm Stat. 2013 Mar 11;23(2):413-24. doi: 10.1080/10543406.2011.616969.
2
Integrating predictive biomarkers and classifiers into oncology clinical development programmes.将预测性生物标志物和分类器整合到肿瘤学临床开发计划中。
Nat Rev Drug Discov. 2011 Sep 30;10(10):735-48. doi: 10.1038/nrd3550.
3
One-step preservation of phosphoproteins and tissue morphology at room temperature for diagnostic and research specimens.一步法室温下保存磷酸化蛋白和组织形态,用于诊断和研究标本。
PLoS One. 2011;6(8):e23780. doi: 10.1371/journal.pone.0023780. Epub 2011 Aug 17.
4
Efficiency of carcinogenesis: is the mutator phenotype inevitable?致癌效率:突变表型是否不可避免?
Semin Cancer Biol. 2010 Oct;20(5):340-52. doi: 10.1016/j.semcancer.2010.10.004. Epub 2010 Oct 8.
5
Randomized clinical trials with biomarkers: design issues.随机临床试验与生物标志物:设计问题。
J Natl Cancer Inst. 2010 Feb 3;102(3):152-60. doi: 10.1093/jnci/djp477. Epub 2010 Jan 14.
6
Sources of bias in specimens for research about molecular markers for cancer.用于癌症分子标志物研究标本的偏倚来源。
J Clin Oncol. 2010 Feb 1;28(4):698-704. doi: 10.1200/JCO.2009.25.6065. Epub 2009 Dec 28.
7
The future of drug development: advancing clinical trial design.药物研发的未来:推进临床试验设计。
Nat Rev Drug Discov. 2009 Dec;8(12):949-57. doi: 10.1038/nrd3025. Epub 2009 Oct 9.
8
Use of archived specimens in evaluation of prognostic and predictive biomarkers.存档标本在评估预后和预测生物标志物中的应用。
J Natl Cancer Inst. 2009 Nov 4;101(21):1446-52. doi: 10.1093/jnci/djp335. Epub 2009 Oct 8.
9
Optimal cost-effective designs of Phase II proof of concept trials and associated go-no go decisions.II期概念验证试验的最优成本效益设计及相关的通过/不通过决策。
J Biopharm Stat. 2009;19(3):424-36. doi: 10.1080/10543400902800478.
10
The use of genomics in clinical trial design.基因组学在临床试验设计中的应用。
Clin Cancer Res. 2008 Oct 1;14(19):5984-93. doi: 10.1158/1078-0432.CCR-07-4531.

用于将预测性生物标志物最佳地整合到肿瘤学临床开发项目中的新的循证适应性临床试验方法。

New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs.

作者信息

Beckman Robert A, Chen Cong

机构信息

Daiichi Sankyo Pharmaceutical Development, Edison, NJ 08837, USA.

出版信息

Chin J Cancer. 2013 May;32(5):233-41. doi: 10.5732/cjc.012.10248. Epub 2013 Mar 15.

DOI:10.5732/cjc.012.10248
PMID:23489587
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3845554/
Abstract

Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict.

摘要

预测性生物标志物对肿瘤学的未来至关重要;它们可用于识别将从治疗中获益的患者群体,提高癌症药物的价值,降低临床试验的规模和成本,同时增加试验成功的机会。但预测性生物标志物并非总能发挥作用。若未成功,它们会增加药物开发的成本、复杂性和时间。本文阐述了2期和3期开发方法,这些方法能有效且适应性地检验生物标志物预测临床结果的能力。最后,生物标志物的重要性在于其实际预测能力。