Clinical trial designs for testing biomarker-based personalized therapies.
Clinical trial designs for testing biomarker-based personalized therapies.
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DOI：
10.1177/1740774512437252
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发表时间：
2012-04
期刊：
影响因子：
--
通讯作者：
Sikic BI
中科院分区：
文献类型：
--
作者：
Lai TL;Lavori PW;Shih MC;Sikic BI
在过去的十年中，分子治疗学的进步为癌症患者的个性化治疗开辟了新的可能性，使用生物标记物来确定哪些治疗最有可能使他们受益，但基于生物标记物的个性化治疗的开发和验证存在困难和悬而未决的问题。我们开发了一种新的临床试验设计来解决其中的一些问题。我们的目标是捕捉频率和贝叶斯方法的优点，以解决最近文献中的这个问题，并绕过它们的局限性。我们使用交集零假设和丰富策略零假设的广义似然比检验来推导出一种新的临床试验设计，以解决将有前途的生物标记物引导的策略推向最终验证的问题。我们还研究了最近文献中提出的自适应随机化(AR)和无效停止的有用性。仿真研究表明，测试与验证所提出的策略相关的狭义聚焦强化策略零假设和能够适应潜在成功策略的交集零假设都具有优势。AR和早期终止无效治疗为试验中的患者提供了更高的接受首选治疗的可能性和更好的应答率，但代价是在总样本量小到中等的情况下进行更复杂的推断，并减少一些功率。在开发阶段使用的二元反应可能不是长期临床结果中治疗益处的可靠指标。在拟议的设计中，生物标记物引导策略(BGS)不与“护理标准”进行比较，例如医生的选择可能会受到患者特征的影响。因此，一个积极的结果并不意味着BGS优于‘护理标准’。所提出的设计和试验是渐近有效的。模拟被用来检查小到中等样本的属性。需要创新的临床试验设计来解决基于生物标记物的个性化治疗的开发和验证中的困难和问题。这篇文章展示了使用似然推断和中期分析来应对所需样本量和不断发展的生物标记物格局以及基因组和蛋白质技术的挑战的优势。
Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations. We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature. Simulation studies demonstrate the advantages of testing both the narrowly focused enriched strategy null hypothesis related to validating a proposed strategy and the intersection null hypothesis that can accommodate to a potentially successful strategy. AR and early termination of ineffective treatments offer increased probability of receiving the preferred treatment and better response rates for patients in the trial, at the expense of more complicated inference under small-to-moderate total sample sizes and some reduction in power. The binary response used in the development phase may not be a reliable indicator of treatment benefit on long-term clinical outcomes. In the proposed design, the biomarker-guided strategy (BGS) is not compared to ‘standard of care’, such as physician’s choice that may be informed by patient characteristics. Therefore, a positive result does not imply superiority of the BGS to ‘standard of care’. The proposed design and tests are valid asymptotically. Simulations are used to examine small-to-moderate sample properties. Innovative clinical trial designs are needed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies. The article shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies.
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DOI：
10.1177/1740774510368574
发表时间：
2010-10
期刊：
Clinical trials (London, England)
影响因子：
--
作者：
Mandrekar SJ;Sargent DJ
通讯作者：
Sargent DJ
影响因子：
45.3
作者：
Korn, Edward L.;Freidlin, Boris
通讯作者：
Freidlin, Boris
影响因子：
28.2
作者：
Kim ES;Herbst RS;Wistuba II;Lee JJ;Blumenschein GR Jr;Tsao A;Stewart DJ;Hicks ME;Erasmus J Jr;Gupta S;Alden CM;Liu S;Tang X;Khuri FR;Tran HT;Johnson BE;Heymach JV;Mao L;Fossella F;Kies MS;Papadimitrakopoulou V;Davis SE;Lippman SM;Hong WK
通讯作者：
Hong WK
影响因子：
4.7
作者：
Penson, RT;Oliva, E;Seiden, MV
通讯作者：
Seiden, MV
影响因子：
6.7
作者：
Barker, A. D.;Sigman, C. C.;Esserman, L. J.
通讯作者：
Esserman, L. J.