Predictive biomarker validation in practice: lessons from real trials.
Predictive biomarker validation in practice: lessons from real trials.
复制标题
DOI：
10.1177/1740774510368574
复制
发表时间：
2010-10
期刊：
影响因子：
--
通讯作者：
Sargent DJ
中科院分区：
文献类型：
--
作者：
Mandrekar SJ;Sargent DJ
随着靶向治疗的出现，生物标志物通过一种综合的方法来预测疾病的基因组成和患者的基因型，为个性化治疗提供了一种很有希望的手段。因此，生物标志物验证已成为医学领域讨论的中心话题，主要是由于疾病治疗方法的变化以及这些疗法的作用机制。在本报告中，我们通过正在进行或已完成的临床试验的例子，讨论了一些用于预测性生物标志物验证的临床试验设计的优点和局限性。设计大致分为回顾性（即使用先前进行良好的随机对照试验（RCT）的数据）和前瞻性（浓缩或靶向，非选择或所有人，混合和适应性分析）。我们将在实际试验的背景下讨论其中的一些设计。设计良好的前瞻性RCT回顾性分析，可以及时对标志物定义的亚组患者提出有效的治疗方案。一个例子是KRAS基因状态在结直肠癌中-西妥昔单抗和帕尼单抗的益处被证明仅限于野生型状态的患者，基于使用先前进行的随机对照试验数据的前瞻性指定分析。当令人信服的初步证据表明并非所有患者都能从考虑的研究治疗中获益时，前瞻性富集设计是合适的；然而，这有时可能会留下一些没有答案的问题。一个例子是曲妥珠单抗作为乳腺癌辅助治疗的既定益处；然而，her2阳性的明确定义和试验的可重复性仍然没有答案。当关于治疗益处和试验可重复性的初步证据不确定时（例如，肺癌中的EGFR表达和酪氨酸激酶抑制剂），或从一组方案中确定最有效的治疗方法（例如，乳腺癌的化疗方案），所有患者的设计是最佳的。这里讨论的设计是基于这样的假设：技术可行性、分析性能指标和标本采集的后勤工作都是很好的建立起来的，并且初步结果显示了关于标记物预测能力的承诺。临床试验设计的选择是由科学、临床、统计和伦理因素综合考虑的。对于预测性生物标志物验证，没有一种万能的解决方案。
With the advent of targeted therapies, biomarkers provide a promising means of individualizing therapy through an integrated approach to prediction using the genetic makeup of the disease and the genotype of the patient. Biomarker validation has therefore become a central topic of discussion in the field of medicine, primarily due to the changing landscape of therapies for treatment of a disease and these therapies purported mechanism(s) of action. In this report, we discuss the merits and limitations of some of the clinical trial designs for predictive biomarker validation using examples from ongoing or completed clinical trials. The designs are broadly classified as retrospective (i.e., using data from previously well-conducted randomized controlled trials (RCT)) versus prospective (enrichment or targeted, unselected or all-comers, hybrid, and adaptive analysis). We discuss some of these designs in the context of real trials. Well-designed retrospective analysis of prospective RCT can bring forward effective treatments to marker defined subgroup of patients in a timely manner. An example is the KRAS gene status in colorectal cancer – the benefit from cetuximab and panitumumab was demonstrated to be restricted to patients with wild type status based on prospectively specified analyses using data from previously conducted RCTs. Prospective enrichment designs are appropriate when compelling preliminary evidence suggests that not all patients will benefit from the study treatment under consideration; however, this may sometimes leave questions unanswered. An example is the established benefit of trastuzumab as adjuvant therapy for breast cancer; a clear definition of HER2-positivity and the assay reproducibility have, however, remained unanswered. An all-comers design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (e.g., EGFR expression and tyrosine kinase inhibitors in lung cancer), or to identify the most effective therapy from a panel of regimens (e.g., chemotherapy options in breast cancer). The designs discussed here rest on the assumption that the technical feasibility, assay performance metrics, and the logistics of specimen collection are well established and that initial results demonstrate promise with regard to the predictive ability of the marker(s). The choice of a clinical trial design is driven by a combination of scientific, clinical, statistical, and ethical considerations. There is no one size fits all solution to predictive biomarker validation.
登录
查看更多内容
影响因子：
45.3
作者：
Eberhard, DA;Johnson, BE;Hillan, KJ
通讯作者：
Hillan, KJ
DOI：
10.1016/s1387-2656(03)09005-7
发表时间：
2003-01-01
期刊：
BIOTECHNOLOGY ANNUAL REVIEW, VOL 9
影响因子：
--
作者：
Paik, S
通讯作者：
Paik, S
影响因子：
--
作者：
Conley, BA;Taube, SE
通讯作者：
Taube, SE
影响因子：
11.5
作者：
Bonomi, Philip D.;Buckingham, Lela;Coon, John
通讯作者：
Coon, John
影响因子：
158.5
作者：
Jonker, Derek J.;O'Callaghan, Chris J.;Moore, Malcolm J.
通讯作者：
Moore, Malcolm J.