Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA.
GenomeDx Biosciences, Vancouver, British Columbia, Canada.
Eur Urol. 2015 Apr;67(4):778-86. doi: 10.1016/j.eururo.2014.10.036. Epub 2014 Nov 12.
Surgery is a standard first-line therapy for men with intermediate- or high-risk prostate cancer. Clinical factors such as tumor grade, stage, and prostate-specific antigen (PSA) are currently used to identify those who are at risk of recurrence and who may benefit from adjuvant therapy, but novel biomarkers that improve risk stratification and that distinguish local from systemic recurrence are needed.
To determine whether adding the Decipher genomic classifier, a validated metastasis risk-prediction model, to standard risk-stratification tools (CAPRA-S and Stephenson nomogram) improves accuracy in predicting metastatic disease within 5 yr after surgery (rapid metastasis [RM]) in an independent cohort of men with adverse pathologic features after radical prostatectomy (RP).
DESIGN, SETTING, AND PARTICIPANTS: The study population consisted of 169 patients selected from 2641 men who underwent RP at the Cleveland Clinic between 1987 and 2008 who met the following criteria: (1) preoperative PSA>20 ng/ml, stage pT3 or margin positive, or Gleason score≥8; (2) pathologic node negative; (3) undetectable post-RP PSA; (4) no neoadjuvant or adjuvant therapy; and (5) minimum of 5-yr follow-up for controls. The final study cohort consisted of 15 RM patients and 154 patients as non-RM controls.
The performance of Decipher was evaluated individually and in combination with clinical risk factors using concordance index (c-index), decision curve analysis, and logistic regression for prediction of RM.
RM patients developed metastasis at a median of 2.3 yr (interquartile range: 1.7-3.3). In multivariable analysis, Decipher was a significant predictor of RM (odds ratio: 1.48; p=0.018) after adjusting for clinical risk factors. Decipher had the highest c-index, 0.77, compared with the Stephenson model (c-index: 0.75) and CAPRA-S (c-index: 0.72) as well as with a panel of previously reported prostate cancer biomarkers unrelated to Decipher. Integration of Decipher into the Stephenson nomogram increased the c-index from 0.75 (95% confidence interval [CI], 0.65-0.85) to 0.79 (95% CI, 0.68-0.89).
Decipher was independently validated as a genomic metastasis signature for predicting metastatic disease within 5 yr after surgery in a cohort of high-risk men treated with RP and managed conservatively without any adjuvant therapy. Integration of Decipher into clinical nomograms increased prediction of RM. Decipher may allow identification of men most at risk for metastatic progression who should be considered for multimodal therapy or inclusion in clinical trials.
Use of Decipher in addition to standard clinical information more accurately identified men who developed metastatic disease within 5 yr after surgery. The results suggest that Decipher allows improved identification of the men who should consider secondary therapy from among the majority that may be managed conservatively after surgery.
手术是中高危前列腺癌患者的标准一线治疗方法。目前,临床因素如肿瘤分级、分期和前列腺特异性抗原(PSA)被用于识别那些有复发风险并可能受益于辅助治疗的患者,但需要新的生物标志物来改善风险分层,并区分局部复发和全身复发。
在克利夫兰诊所接受根治性前列腺切除术(RP)的具有不利病理特征的男性中,确定是否通过添加验证的转移风险预测模型 Decipher 基因组分类器来提高标准风险分层工具(CAPRA-S 和 Stephenson 列线图)预测术后 5 年内(快速转移[RM])发生转移性疾病的准确性。
设计、地点和参与者:研究人群由 1987 年至 2008 年间在克利夫兰诊所接受 RP 的 2641 名男性中选择的 169 名患者组成,这些患者符合以下标准:(1)术前 PSA>20ng/ml,分期 pT3 或边缘阳性,或 Gleason 评分≥8;(2)病理淋巴结阴性;(3)术后 PSA 无法检测;(4)无新辅助或辅助治疗;(5)对照组的随访时间至少为 5 年。最终研究队列包括 15 名 RM 患者和 154 名非 RM 对照组患者。
使用一致性指数(c-index)、决策曲线分析和逻辑回归,评估 Decipher 单独和与临床危险因素联合预测 RM 的性能。
RM 患者在中位数为 2.3 年(四分位距:1.7-3.3)时发生转移。在多变量分析中,在调整临床危险因素后,Decipher 是 RM 的显著预测因子(比值比:1.48;p=0.018)。与 Stephenson 模型(c-index:0.75)和 CAPRA-S(c-index:0.72)相比,Decipher 的 c-index 最高,为 0.77,并且与之前报道的与 Decipher 无关的前列腺癌生物标志物面板相比,也具有最高的 c-index。将 Decipher 整合到 Stephenson 列线图中,使 c-index 从 0.75(95%置信区间[CI]:0.65-0.85)增加到 0.79(95%CI:0.68-0.89)。
在接受 RP 治疗且未接受任何辅助治疗的保守治疗的高危男性队列中,Decipher 作为一种独立的基因组转移特征,可验证预测术后 5 年内发生转移疾病的能力。将 Decipher 整合到临床列线图中增加了 RM 的预测能力。Decipher 可能有助于识别最有可能发生转移进展的男性,这些患者应考虑接受多模式治疗或纳入临床试验。
使用 Decipher 联合标准临床信息可更准确地识别出术后 5 年内发生转移性疾病的男性。研究结果表明,Decipher 可改善大多数可能在手术后接受保守治疗的患者中识别出需要辅助治疗的男性。