Cancer Prevention Program, Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA.
Department of Urology, University of Washington, Seattle, WA.
J Clin Oncol. 2020 May 10;38(14):1549-1557. doi: 10.1200/JCO.19.02267. Epub 2020 Mar 4.
The 17-gene Onco DX Genomic Prostate Score (GPS) test predicts adverse pathology (AP) in patients with low-risk prostate cancer treated with immediate surgery. We evaluated the GPS test as a predictor of outcomes in a multicenter active surveillance cohort.
Diagnostic biopsy tissue was obtained from men enrolled at 8 sites in the Canary Prostate Active Surveillance Study. The primary endpoint was AP (Gleason Grade Group [GG] ≥ 3, ≥ pT3a) in men who underwent radical prostatectomy (RP) after initial surveillance. Multivariable regression models for interval-censored data were used to evaluate the association between AP and GPS. Inverse probability of censoring weighting was applied to adjust for informative censoring. Predictiveness curves were used to evaluate how models stratified risk of AP. Association between GPS and time to upgrade on surveillance biopsy was evaluated using Cox proportional hazards models.
GPS results were obtained for 432 men (median follow-up, 4.6 years); 101 underwent RP after a median 2.1 years of surveillance, and 52 had AP. A total of 167 men (39%) upgraded at a subsequent biopsy. GPS was significantly associated with AP when adjusted for diagnostic GG (hazards ratio [HR]/5 GPS units, 1.18; 95% CI, 1.04 to 1.44; = .030), but not when also adjusted for prostate-specific antigen density (PSAD; HR, 1.85; 95% CI, 0.99 to 4.19; = .066). Models containing PSAD and GG, or PSAD, GG, and GPS may stratify risk better than a model with GPS and GG. No association was observed between GPS and subsequent biopsy upgrade ( = .48).
In our study, the independent association of GPS with AP after initial active surveillance was not statistically significant, and there was no association with upgrading in surveillance biopsy. Adding GPS to a model containing PSAD and diagnostic GG did not significantly improve stratification of risk for AP over the clinical variables alone.
17 基因 Onco DX 基因组前列腺评分（GPS）检测可预测接受即刻手术治疗的低危前列腺癌患者的不良病理（AP）。我们评估了 GPS 检测在多中心主动监测队列中的预测结果。
从 Canary 前列腺主动监测研究中 8 个站点入组的男性中获取诊断性活检组织。主要终点为初始监测后行根治性前列腺切除术（RP）的男性中 AP（Gleason 分级分组 [GG]≥3，≥pT3a）。使用间隔 censored 数据的多变量回归模型评估 AP 与 GPS 之间的相关性。应用逆概率 censoring 加权法调整有信息 censoring 的影响。预测曲线用于评估模型如何分层 AP 风险。使用 Cox 比例风险模型评估 GPS 与监测活检升级之间的关系。
共获得 432 名男性的 GPS 结果（中位随访时间 4.6 年）；中位随访 2.1 年后 101 名男性接受 RP，52 名男性发生 AP。共有 167 名男性（39%）在后续活检中升级。GPS 在调整诊断性 GG 后与 AP 显著相关（每增加 5 GPS 单位的危险比 [HR]，1.18；95%置信区间，1.04 至 1.44； =.030），但在调整前列腺特异性抗原密度（PSAD）后不相关（HR，1.85；95%置信区间，0.99 至 4.19； =.066）。包含 PSAD 和 GG 的模型，或包含 PSAD、GG 和 GPS 的模型，可能比仅包含 GPS 和 GG 的模型更好地分层风险。GPS 与后续活检升级之间无相关性（ =.48）。
在我们的研究中，GPS 与初始主动监测后 AP 的独立相关性无统计学意义，且与监测活检升级无相关性。在包含 PSAD 和诊断性 GG 的模型中添加 GPS 并不能显著提高 AP 风险分层的效果，优于仅使用临床变量。
