Molecular Imaging Branch, NCI, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892.
Urologic Oncology Branch, NCI, NIH, Bethesda, MD.
AJR Am J Roentgenol. 2023 Dec;221(6):773-787. doi: 10.2214/AJR.23.29609. Epub 2023 Jul 5.
Currently most clinical models for predicting biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) incorporate staging information from RP specimens, creating a gap in preoperative risk assessment. The purpose of our study was to compare the utility of presurgical staging information from MRI and postsurgical staging information from RP pathology in predicting BCR in patients with PCa. This retrospective study included 604 patients (median age, 60 years) with PCa who underwent prostate MRI before RP from June 2007 to December 2018. A single genitourinary radiologist assessed MRI examinations for extraprostatic extension (EPE) and seminal vesicle invasion (SVI) during clinical interpretations. The utility of EPE and SVI on MRI and RP pathology for BCR prediction was assessed through Kaplan-Meier and Cox proportional hazards analyses. Established clinical BCR prediction models, including the University of California San Francisco Cancer of the Prostate Risk Assessment (UCSF-CAPRA) model and the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) model, were evaluated in a subset of 374 patients with available Gleason grade groups from biopsy and RP pathology; two CAPRA-MRI models (CAPRA-S model with modifications to replace RP pathologic staging features with MRI staging features) were also assessed. Univariable predictors of BCR included EPE on MRI (HR = 3.6), SVI on MRI (HR = 4.4), EPE on RP pathology (HR = 5.0), and SVI on RP pathology (HR = 4.6) (all < .001). Three-year BCR-free survival (RFS) rates for patients without versus with EPE were 84% versus 59% for MRI and 89% versus 58% for RP pathology, and 3-year RFS rates for patients without versus with SVI were 82% versus 50% for MRI and 83% versus 54% for RP histology (all < .001). For patients with T3 disease on RP pathology, 3-year RFS rates were 67% and 41% for patients without and with T3 disease on MRI. AUCs of CAPRA models, including CAPRA-MRI models, ranged from 0.743 to 0.778. AUCs were not significantly different between CAPRA-S and CAPRA-MRI models ( > .05). RFS rates were significantly different between low- and intermediate-risk groups for only CAPRA-MRI models (80% vs 51% and 74% vs 44%; both < .001). Presurgical MRI-based staging features perform comparably to postsurgical pathologic staging features for predicting BCR. MRI staging can preoperatively identify patients at high BCR risk, helping to inform early clinical decision-making. ClinicalTrials.gov NCT00026884 and NCT02594202.
目前,大多数用于预测前列腺癌根治术后生化复发(BCR)的临床模型都纳入了 RP 标本的分期信息,这在术前风险评估中造成了差距。我们的研究目的是比较 MRI 术前分期信息和 RP 病理术后分期信息在预测前列腺癌患者 BCR 中的作用。这项回顾性研究纳入了 604 名(中位年龄 60 岁)于 2007 年 6 月至 2018 年 12 月期间接受前列腺 MRI 检查的前列腺癌患者。一名泌尿生殖放射科医生在临床解读期间评估 MRI 检查的前列腺外扩展(EPE)和精囊侵犯(SVI)。通过 Kaplan-Meier 和 Cox 比例风险分析评估 MRI 和 RP 病理中的 EPE 和 SVI 在 BCR 预测中的作用。在 374 名具有活检和 RP 病理中可获得的格里森分级组的患者亚组中评估了既定的临床 BCR 预测模型,包括加利福尼亚大学旧金山前列腺癌风险评估(UCSF-CAPRA)模型和前列腺癌风险评估术后(CAPRA-S)模型;还评估了两种 CAPRA-MRI 模型(用修改后的 CAPRA-S 模型替换 RP 病理分期特征以替换 MRI 分期特征)。BCR 的单变量预测因素包括 MRI 上的 EPE(HR=3.6)、MRI 上的 SVI(HR=4.4)、RP 病理上的 EPE(HR=5.0)和 RP 病理上的 SVI(HR=4.6)(均<0.001)。无 EPE 患者与有 EPE 患者的 3 年 BCR 无复发生存率(RFS)分别为 84%和 59%(MRI)和 89%和 58%(RP 病理),无 SVI 患者与有 SVI 患者的 3 年 RFS 率分别为 82%和 50%(MRI)和 83%和 54%(RP 组织学)(均<0.001)。对于 RP 病理上有 T3 疾病的患者,无 T3 疾病和有 T3 疾病患者的 3 年 RFS 率分别为 67%和 41%。CAPRA 模型(包括 CAPRA-MRI 模型)的 AUC 范围为 0.743 至 0.778。CAPRA-S 和 CAPRA-MRI 模型之间的 AUC 没有显著差异(>0.05)。仅 CAPRA-MRI 模型的低危和中危组之间的 RFS 率有显著差异(80%比 51%和 74%比 44%;均<0.001)。术前 MRI 分期特征与术后病理分期特征在预测 BCR 方面具有可比性。MRI 分期可在术前识别出 BCR 风险高的患者,有助于指导早期临床决策。ClinicalTrials.gov NCT00026884 和 NCT02594202。