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基于多参数磁共振成像检查结果,为国际泌尿病理学会(ISUP)分级分组(GG)1 或 ISUP GG2 前列腺癌患者制定的主动监测候选者的新型列线图。

A novel nomogram to identify candidates for active surveillance amongst patients with International Society of Urological Pathology (ISUP) Grade Group (GG) 1 or ISUP GG2 prostate cancer, according to multiparametric magnetic resonance imaging findings.

机构信息

Department of Urology, IEO European Institute of Oncology, IRCCS, Milan, Italy.

Università degli Studi di Milano, Milan, Italy.

出版信息

BJU Int. 2020 Jul;126(1):104-113. doi: 10.1111/bju.15048. Epub 2020 Apr 1.

Abstract

OBJECTIVES

To develop a novel nomogram to identify candidates for active surveillance (AS) that combines clinical, biopsy and multiparametric magnetic resonance imaging (mpMRI) findings; and to compare its predictive accuracy to, respectively: (i) Prostate Cancer Research International: Active Surveillance (PRIAS) criteria, (ii) Johns Hopkins (JH) criteria, (iii) European Association of Urology (EAU) low-risk classification, and (iv) EAU low-risk or low-volume with International Society of Urological Pathology (ISUP) Grade Group (GG) 2 classification.

PATIENTS AND METHODS

We selected 1837 patients with ISUP GG1 or GG2 prostate cancer (PCa), treated with radical prostatectomy (RP) between 2012 and 2018. The outcome of interest was the presence of unfavourable disease (i.e., clinically significant PCa [csPCa]) at RP, defined as: ISUP GG 3 and/or pathological T stage (pT) ≥3a and/or pathological N stage (pN) 1. First, logistic regression models including PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 binary classifications (not eligible vs eligible) were used. Second, a multivariable logistic regression model including age, prostate-specific antigen density (PSA-D), ISUP GG, and the percentage of positive cores (Model 1) was fitted. Third, Prostate Imaging-Reporting and Data System (PI-RADS) score (Model 2), extracapsular extension (ECE) score (Model 3) and PI-RADS + ECE score (Model 4) were added to Model 1. Only variables associated with higher csPCa rates in Model 4 were retained in the final simplified Model 5. The area under the receiver operating characteristic curve (AUC), calibration plots and decision curve analyses were used.

RESULTS

Of the 1837 patients, 775 (42.2%) had csPCa at RP. Overall, 837 (47.5%), 986 (53.7%), 348 (18.9%), and 209 (11.4%) patients were eligible for AS according to, respectively, the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS, and JH criteria. The proportion of csPCa amongst the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS and JH candidates was, respectively 28.5%, 29.3%, 25.6% and 17.2%. Model 4 and Model 5 (in which only PSA-D, ISUP GG, PI-RADS and ECE score were retained) had a greater AUC (0.84), compared to the four proposed AS criteria (all P < 0.001). The adoption of a 25% nomogram threshold increased the proportion of AS-eligible patients from 18.9% (PRIAS) and 11.4% (JH) to 44.4%. Moreover, the same 25% nomogram threshold resulted in significantly lower estimated risks of csPCa (11.3%), compared to PRIAS (Δ: -14.3%), JH (Δ: -5.9%), EAU low-risk (Δ: -17.2%), and EAU low-risk or low-volume ISUP GG2 classifications (Δ: -18.0%).

CONCLUSION

The novel nomogram combining clinical, biopsy and mpMRI findings was able to increase by ~25% and 35% the absolute frequency of patients suitable for AS, compared to, respectively, the PRIAS or JH criteria. Moreover, this nomogram significantly reduced the estimated frequency of csPCa that would be recommended for AS compared to, respectively, the PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 classifications.

摘要

目的:建立一种新的列线图,用于识别适合主动监测(AS)的候选者,该列线图结合了临床、活检和多参数磁共振成像(mpMRI)的发现;并分别与(i)前列腺癌研究国际:主动监测(PRIAS)标准、(ii)约翰霍普金斯(JH)标准、(iii)欧洲泌尿外科学会(EAU)低风险分类以及(iv)EAU 低风险或低体积与国际泌尿病理学会(ISUP)分级组(GG)2 分类进行比较,以评估其预测准确性。

患者和方法:我们选择了 1837 名 ISUP GG1 或 GG2 前列腺癌(PCa)患者,他们在 2012 年至 2018 年间接受了根治性前列腺切除术(RP)治疗。感兴趣的结果是 RP 时存在不良疾病(即临床显著前列腺癌 [csPCa]),定义为:ISUP GG 3 和/或病理 T 期(pT)≥3a 和/或病理 N 期(pN)1。首先,使用包括 PRIAS、JH、EAU 低风险和 EAU 低风险或低体积 ISUP GG2 二进制分类(不合格与合格)的逻辑回归模型。其次,拟合包括年龄、前列腺特异性抗原密度(PSA-D)、ISUP GG 和阳性核心百分比(模型 1)的多变量逻辑回归模型。第三,添加前列腺成像报告和数据系统(PI-RADS)评分(模型 2)、包膜外延伸(ECE)评分(模型 3)和 PI-RADS+ECE 评分(模型 4)到模型 1 中。仅在模型 4 中与更高的 csPCa 发生率相关的变量保留在最终简化的模型 5 中。使用接收者操作特征曲线(ROC)曲线下面积(AUC)、校准图和决策曲线分析。

结果:在 1837 名患者中,775 名(42.2%)在 RP 时患有 csPCa。总体而言,根据 EAU 低风险、EAU 低风险或低体积 ISUP GG2、PRIAS 和 JH 标准,分别有 837(47.5%)、986(53.7%)、348(18.9%)和 209(11.4%)名患者有资格接受 AS。EAU 低风险、EAU 低风险或低体积 ISUP GG2、PRIAS 和 JH 候选者中 csPCa 的比例分别为 28.5%、29.3%、25.6%和 17.2%。与四个提出的 AS 标准(均 P<0.001)相比,模型 4 和模型 5(其中仅保留 PSA-D、ISUP GG、PI-RADS 和 ECE 评分)具有更大的 AUC(0.84)。采用 25%的列线图阈值,将符合 AS 条件的患者比例从 PRIAS(18.9%)和 JH(11.4%)分别提高到 44.4%。此外,相同的 25%列线图阈值导致 csPCa 的估计风险显著降低(11.3%),与 PRIAS(Δ:-14.3%)、JH(Δ:-5.9%)、EAU 低风险(Δ:-17.2%)和 EAU 低风险或低体积 ISUP GG2 分类(Δ:-18.0%)相比。

结论:结合临床、活检和 mpMRI 发现的新列线图能够将符合 AS 条件的患者的绝对频率分别提高~25%和 35%,与 PRIAS 或 JH 标准相比。此外,与 PRIAS、JH、EAU 低风险和 EAU 低风险或低体积 ISUP GG2 分类相比,该列线图显著降低了推荐用于 AS 的 csPCa 的估计频率。

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