Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany; Berta-Ottenstein-Programme, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Department of Radiation Oncology, University Hospitals Leuven, Belgium; Department of Oncology, KU Leuven, Belgium.
Int J Radiat Oncol Biol Phys. 2023 Jul 1;116(3):503-520. doi: 10.1016/j.ijrobp.2022.12.038. Epub 2022 Dec 31.
Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk stratification after surgery, but less data exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) a survey of experts using the Delphi method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research. We performed a systematic review and screened ongoing clinical trials on ClinicalTrials.gov. Based on these results, a multidisciplinary international team of experts received an adapted Delphi method survey. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa.
目前用于前列腺癌（PCa）的风险分层系统并不能充分反映疾病的异质性。基因组分类器（GC）能够在手术后实现更好的风险分层，但在接受确定性放射治疗（RT）或寡转移/转移性疾病阶段 RT 的患者中，相关数据较少。为了指导 GC 用于 RT 的未来前景，我们进行了（1）系统回顾 GC 用于接受 RT 治疗的患者的证据，（2）使用 Delphi 方法对专家进行调查，以确定 GC 在个性化治疗中的作用，以确定未来临床和转化研究的相关领域。我们在 ClinicalTrials.gov 上进行了系统回顾和筛选正在进行的临床试验。基于这些结果，一个由多学科国际专家组成的团队收到了一份经过调整的 Delphi 方法调查。分别有 31 名和 30 名专家回答了第一轮和第二轮调查。得到≥75%的专家同意的问题被认为是相关的，并纳入了定性综合分析。GC 作为预测生物标志物的证据主要在术后 RT 环境中可用。GC 作为确定性 RT 环境中预后标志物的验证正在出现。专家在广泛转移的 PCa 患者（30%）、术后环境（27%）和新诊断的 PCa 患者（23%）中使用 GC。47%的专家目前不在临床实践中使用 GC。专家共识表明，GC 是一种有前途的工具，可以在现有分类的基础上，改善原发性和寡转移/转移性患者的风险分层。专家们确信，GC 可以指导 RT 领域定义和强化/减量化治疗决策，在各种疾病阶段。这项工作证实了 GC 的价值和 GC 在 RT 环境中应用的有前途的证据。预计将对 GC 作为预后生物标志物的研究进行更多研究，并为未来研究 GC 预测能力以优化 RT 和系统治疗奠定基础。专家共识指出了 GC 研究在 PCa 管理中的未来方向。
