Department of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands.
Department of Molecular Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands.
Cancer Treat Rev. 2017 Jan;52:117-127. doi: 10.1016/j.ctrv.2016.11.008. Epub 2016 Nov 30.
Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical validity and clinical utility. While attaining analytical and clinical validity is relatively straightforward, by following methodological recommendations, the achievement of clinical utility is extremely challenging. It requires demonstrating three associations: the biomarker with the outcome (prognostic association), the effect of treatment independent of the biomarker, and the differential treatment effect between the prognostic and the predictive biomarker (predictive association). In addition, economical, ethical, regulatory, organizational and patient/doctor-related aspects are hampering the translational process. Traditionally, these aspects do not receive much attention until formal approval or reimbursement of a biomarker test (informed by Health Technology Assessment (HTA)) is at stake, at which point the clinical utility and sometimes price of the test can hardly be influenced anymore. When HTA analyses are performed earlier, during biomarker research and development, they may prevent further development of those biomarkers unlikely to ever provide sufficient added value to society, and rather facilitate translation of the promising ones. Early HTA is particularly relevant for the predictive biomarker field, as expensive medicines are under pressure and the need for biomarkers to guide their appropriate use is huge. Closer interaction between clinical researchers and HTA experts throughout the translational research process will ensure that available data and methodologies will be used most efficiently to facilitate biomarker translation.
预测性生物标志物可以指导乳腺癌的治疗决策。许多研究都致力于发现和转化这些生物标志物,但很少有生物标志物能付诸实践。在用于临床决策之前,预测性生物标志物需要证明分析有效性、临床有效性和临床实用性。虽然获得分析和临床有效性相对简单,只要遵循方法学建议,但实现临床实用性极具挑战性。这需要证明三个关联:生物标志物与结果(预后关联)、独立于生物标志物的治疗效果,以及预后生物标志物和预测生物标志物之间的治疗效果差异(预测关联)。此外,经济、伦理、监管、组织和患者/医生相关方面也在阻碍转化过程。传统上,这些方面在正式批准或报销生物标志物检测(由健康技术评估(HTA)告知)受到威胁之前,并没有得到太多关注,此时检测的临床实用性和有时价格几乎无法再产生影响。当 HTA 分析在生物标志物研究和开发期间更早进行时,它们可能会阻止那些不太可能为社会带来足够附加值的生物标志物进一步开发,而是促进有前途的生物标志物的转化。早期 HTA 对于预测性生物标志物领域尤为重要,因为昂贵的药物面临压力,需要生物标志物来指导其合理使用。在整个转化研究过程中,临床研究人员和 HTA 专家之间更密切的互动将确保充分利用现有数据和方法,以促进生物标志物的转化。