Kwatra Shawn G, Hines Howard, Semenov Yevgeniy R, Trotter Shannon C, Holland Elizabeth, Leachman Sancy
Dr. Kwatra is Assistant Professor of Dermatology at the Johns Hopkins University School of Medicine in Baltimore, Maryland.
Dr. Hines is Assistant Professor of Dermatology at Johns Hopkins University School of Medicine in Baltimore, Maryland.
J Clin Aesthet Dermatol. 2020 Nov;13(11 Suppl 1):s3-s14. Epub 2020 Nov 1.
With the advent of effective therapeutics, melanoma mortality rates have decreased, yet incidence rates are continuing to rise, making accurate prognostication for risk of recurrence increasingly important. Gene expression profiling (GEP) is a clinically available, objective metric that can be used in conjunction with traditional clinicopathological staging to help physicians stratify risk in melanoma patients. There is a gap in guidance from the American Joint Committee on Cancer (AJCC) and the National Comprehensive Cancer Network (NCCN) regarding how to utilize GEP in melanoma care. An expert panel of 31-GEP test users sought to provide clarification of use options and a rational clinical workflow to guide appropriate application of the 31- GEP test in everyday practice. The authors participated in an in-depth review of the literature and panel discussion regarding current limitations of melanoma risk assessment and opportunities for improvement with GEP. The panel reviewed 1) validation and clinical impact data supporting the use of sentinel lymph node biopsy (SLNB), 2) existing primary data and meta-analyses for 31-GEP testing in melanoma risk assessment, 3) AJCC, NCCN, and Melanoma Prevention Working Group (MPWG) data and guidelines for GEP use in melanoma risk assessment, and 4) experiences, rationales, and scenarios in which 31-GEP testing may be helpful for risk assessment. The 31-GEP test is useful and actionable for patient care when applied in accordance with current NCCN guidelines. Stratification of patients into low (Class 1a), intermediate (Class 1b or 2a), or high (Class 2b) risk categories can inform multidisciplinary conference discussion and can assist with determining the intensity of imaging, surveillance, and follow-up care. Patient-specific features of the disease and individual circumstances should be considered in the decision to use 31-GEP testing. The authors suggest a clinical workflow that integrates 31-GEP testing under the umbrella of current national guidelines. Application of the test in appropriate patient populations can improve risk assessment and inform clinical decision-making.
随着有效治疗方法的出现,黑色素瘤死亡率有所下降,但发病率仍在持续上升,因此准确预测复发风险变得越来越重要。基因表达谱分析(GEP)是一种临床可用的客观指标,可与传统的临床病理分期相结合,帮助医生对黑色素瘤患者的风险进行分层。美国癌症联合委员会(AJCC)和美国国立综合癌症网络(NCCN)在如何将GEP应用于黑色素瘤治疗方面的指导存在差距。一个由31-GEP检测使用者组成的专家小组试图阐明使用选项,并提供合理的临床工作流程,以指导在日常实践中正确应用31-GEP检测。作者参与了对文献的深入回顾以及关于黑色素瘤风险评估当前局限性和GEP改善机会的小组讨论。该小组审查了:1)支持前哨淋巴结活检(SLNB)使用的验证和临床影响数据;2)黑色素瘤风险评估中31-GEP检测的现有原始数据和荟萃分析;3)AJCC、NCCN和黑色素瘤预防工作组(MPWG)关于GEP在黑色素瘤风险评估中使用的数据和指南;4)31-GEP检测可能有助于风险评估的经验、基本原理和场景。按照当前NCCN指南应用时,31-GEP检测对患者护理是有用且可行的。将患者分为低风险(1a类)、中风险(1b类或2a类)或高风险(2b类)类别,可以为多学科会议讨论提供信息,并有助于确定影像学、监测和后续护理的强度。在决定使用31-GEP检测时,应考虑疾病的患者特异性特征和个体情况。作者建议了一种在当前国家指南框架下整合31-GEP检测的临床工作流程。在合适的患者群体中应用该检测可以改善风险评估并为临床决策提供依据。