Division of Population Health, Health Services Research & Primary Care Centre, University of Manchester, Manchester, UK.
Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
BMC Cancer. 2022 Aug 11;22(1):878. doi: 10.1186/s12885-022-09955-w.
Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population.
Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm.
Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame).
MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available.
在非转移性前列腺癌中，治疗前风险和预后分组是决定管理方案的基石。然而，所有这些分组都是在 MRI 出现之前制定的。在这里，我们比较了在未筛查人群中，仅使用临床参数或使用 MRI 增强信息对前列腺癌患者进行分类的情况。
本研究使用了从初级保健机构转介到我们诊断服务机构的男性的数据，这些数据包括临床（直肠指检 [DRE] 和系统活检）和 MRI 增强特征（MRI 分期和系统/靶向活检组合）。使用欧洲泌尿外科学会 (EAU)、美国泌尿外科学会 (AUA) 和英国国家卫生与保健卓越研究所 (NICE) 剑桥预后分组 (CPG) 模型，比较了临床与 MRI 数据在临床病理和风险组再分配方面的差异。将差异回退到具有长期前列腺癌死亡率 (PCM) 结果的人群队列中，以模拟对模型性能的影响。我们还使用 PredictProstate 算法进一步比较了个体总生存 (OS) 预测。
本研究纳入了 370 名男性的数据（中位年龄 66 岁）。术前 MRI 分期重新分配的发生率为 7.8%（与 DRE 相比）。图像引导活检分别使 2.7%和 2.9%的分级组 2 和≥分级组 3 分配增加。风险组的主要变化是更多的高危癌症（EAU 和 AUA 系统增加 6.2%，CPG4 增加 4.3%，CPG5 增加 1.9%）。当外推到基于人群的历史队列（n=10139）时，再分配导致 PCM 的一致性指数普遍降低。5 级 NICE-CPG 系统优于 4 级 AUA 和 3 级 EAU 模型（C 指数分别为 0.70、0.65 和 0.64）。使用个体化预后模型，预测 OS 的变化很小（10 年和 15 年的中位数差异分别为 1%和 2%）。同样，估计的治疗生存获益变化也很小（10 年和 15 年的时间框架均为 1%）。
MRI 引导的诊断确实改变了治疗前的风险组分配，但在未筛查人群中，总体预后影响似乎不大。特别是当使用更细粒度的分层或个体化预后模型时。在获得长期生存结果之前，可以继续使用现有的风险和预后模型来为男性提供关于治疗选择的咨询。
