Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Int J Radiat Oncol Biol Phys. 2016 May 1;95(1):30-36. doi: 10.1016/j.ijrobp.2015.10.004. Epub 2015 Oct 9.
Reducing dose to normal tissues is the advantage of protons versus photons. We aimed to describe a method for translating this reduction into a clinically relevant benefit.
Dutch scientific and health care governance bodies have recently issued landmark reports regarding generation of relevant evidence for new technologies in health care including proton therapy. An approach based on normal tissue complication probability (NTCP) models has been adopted to select patients who are most likely to experience fewer (serious) adverse events achievable by state-of-the-art proton treatment.
By analogy with biologically targeted therapies, the technology needs to be tested in enriched cohorts of patients exhibiting the decisive predictive marker: difference in normal tissue dosimetric signatures between proton and photon treatment plans. Expected clinical benefit is then estimated by virtue of multifactorial NTCP models. In this sense, high-tech radiation therapy falls under precision medicine. As a consequence, randomizing nonenriched populations between photons and protons is predictably inefficient and likely to produce confusing results.
Validating NTCP models in appropriately composed cohorts treated with protons should be the primary research agenda leading to urgently needed evidence for proton therapy.
相较于光子,质子治疗的优势在于能够降低正常组织的剂量。我们旨在描述一种将这种降低转化为临床相关获益的方法。
荷兰科学和医疗保健管理机构最近发布了具有里程碑意义的报告,涉及为包括质子治疗在内的医疗新技术生成相关证据。该方法基于正常组织并发症概率(NTCP)模型,用于选择最有可能通过最先进的质子治疗实现更少(严重)不良事件的患者。
与针对生物靶区的治疗类似,该技术需要在具有决定性预测标志物的富集患者队列中进行测试:质子和光子治疗计划之间的正常组织剂量特征差异。然后通过多因素 NTCP 模型估计预期的临床获益。从这个意义上讲,高科技放射治疗属于精准医疗。因此,在光子和质子之间对非富集人群进行随机分组预计效率低下,并且可能产生混乱的结果。
在接受质子治疗的适当组成队列中验证 NTCP 模型应成为主要的研究议程,以提供质子治疗急需的证据。