Pettersson Andreas, Gerke Travis, Fall Katja, Pawitan Yudi, Holmberg Lars, Giovannucci Edward L, Kantoff Philip W, Adami Hans-Olov, Rider Jennifer R, Mucci Lorelei A
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Clinical Epidemiology Unit, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.
Cancer. 2017 May 1;123(9):1490-1496. doi: 10.1002/cncr.30582. Epub 2017 Feb 2.
There has been limited success in identifying prognostic biomarkers in prostate cancer. A partial explanation may be that insufficient emphasis has been put on clearly defining what type of marker or patient category a biomarker study aims to identify and how different cohort characteristics affect the ability to identify such a marker. In this article, the authors put forth the ABC model of prostate cancer, which defines 3 groups of patients with localized disease that an investigator may seek to identify: patients who, within a given time frame, will not develop metastases even if untreated (category A), will not develop metastases because of radical treatment (category B), or will develop metastases despite radical treatment (category C). The authors demonstrate that follow-up time and prostate-specific antigen screening intensity influence the prevalence of patients in categories A, B, and C in a study cohort, and that prognostic markers must be tested in both treated and untreated cohorts to accurately distinguish the 3 groups. The authors suggest that more emphasis should be put on considering these factors when planning, conducting, and interpreting the results from prostate cancer biomarker studies, and propose the ABC model as a framework to aid in that process. Cancer 2017;123:1490-1496. © 2017 American Cancer Society.
在前列腺癌中,识别预后生物标志物方面取得的成功有限。部分原因可能是,对于明确界定生物标志物研究旨在识别何种类型的标志物或患者类别,以及不同队列特征如何影响识别此类标志物的能力,人们关注不足。在本文中,作者提出了前列腺癌的ABC模型,该模型定义了研究者可能试图识别的3组局限性疾病患者:在给定时间内,即使未经治疗也不会发生转移的患者(A类)、因根治性治疗而不会发生转移的患者(B类),或尽管接受了根治性治疗仍会发生转移的患者(C类)。作者表明,随访时间和前列腺特异性抗原筛查强度会影响研究队列中A、B、C三类患者的比例,并且必须在接受治疗和未接受治疗的队列中对预后标志物进行检测,才能准确区分这3组患者。作者建议,在规划、开展和解释前列腺癌生物标志物研究结果时,应更加重视考虑这些因素,并提出ABC模型作为有助于这一过程的框架。《癌症》2017年;123:1490 - 1496。©2017美国癌症协会