Unit of Urology/Division of Oncology, URI, IRCCS Ospedale San Raffaele, Milan, Italy.
Department of Urology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
BJU Int. 2018 Nov;122(5):823-830. doi: 10.1111/bju.14391. Epub 2018 Jun 3.
To develop a novel tool to increase the number of patients with prostate cancer eligible for active surveillance (AS) without increasing the risk of unfavourable pathological features (i.e., misclassification) at radical prostatectomy (RP).
Overall, 16 049 patients with low- or intermediate-risk prostate cancer treated with RP were identified. Misclassification was defined as non-organ confined or grade group ≥3 disease at RP. The coefficients of a logistic regression model predicting misclassification were used to develop a risk score. We then performed a systematic analysis of different thresholds to discriminate between patients with or without unfavourable disease and we compared it to available AS criteria.
Overall, 5289 (33.0%) patients had unfavourable disease. At multivariable analyses, PSA level, clinical stage, biopsy grade group, the number of positive cores, and PSA density were associated with the risk of unfavourable disease (all P < 0.001). The Prostate Cancer Research International: Active Surveillance (PRIAS) criteria were associated with a lower risk of misclassification (13%) compared to other criteria. Overall, 3303 (20.6%) patients were eligible according to the PRIAS protocol. The adoption of an 18% threshold according to the risk score increased the proportion of eligible patients from 20.6% to 29.4% without increasing the risk of misclassification as compared to the PRIAS criteria.
The use of a novel risk score for AS selection would result in an absolute increase of 10% in the number of patients eligible for this approach without increasing the risk of misclassification.
开发一种新工具,在不增加接受主动监测(AS)的前列腺癌患者数量的情况下增加风险(即分类错误),而不增加接受根治性前列腺切除术(RP)的患者数量。
共确定了 16049 例接受 RP 治疗的低危或中危前列腺癌患者。分类错误定义为 RP 时非器官受限或分级组≥3 疾病。用于预测分类错误的逻辑回归模型的系数用于开发风险评分。然后,我们对不同的阈值进行了系统分析,以区分有或没有不良疾病的患者,并将其与现有的 AS 标准进行了比较。
总体而言,5289 例(33.0%)患者存在不良疾病。多变量分析显示,PSA 水平、临床分期、活检分级组、阳性核心数和 PSA 密度与不良疾病的风险相关(均 P < 0.001)。前列腺癌研究国际:主动监测(PRIAS)标准与其他标准相比,分类错误的风险较低(13%)。总体而言,根据 PRIAS 方案,有 3303 例(20.6%)患者符合条件。与 PRIAS 标准相比,采用 18%的风险评分阈值将符合条件的患者比例从 20.6%增加到 29.4%,而不会增加分类错误的风险。
使用新的 AS 选择风险评分将导致符合该方法的患者数量绝对增加 10%,而不会增加分类错误的风险。