Li Eric V, Kumar Sai, Aguiar Jonathan A, Siddiqui Mohammad R, Sun Zequn, Neill Clayton, Schaeffer Edward M, Ross Ashley E, Patel Hiten D
Northwestern University, Feinberg School of Medicine, Department of Urology, Chicago, IL, 60611, USA.
Northwestern University, Feinberg School of Medicine, Department of Preventive Medicine-Division of Biostatistics, Chicago, IL, 60611, USA.
Prostate Cancer Prostatic Dis. 2025 Jan 7. doi: 10.1038/s41391-024-00928-7.
Traditional nomograms can inform the presence of extraprostatic extension (EPE) but not laterality, which remains important for surgical planning, and have not fully incorporated multiparametric MRI data. We evaluated predictors of side-specific EPE on surgical pathology including MRI characteristics and developed side-specific EPE risk calculators.
This was a retrospective cohort of patients evaluated with mpMRI prior to radical prostatectomy (RP) in our eleven hospital healthcare system from July 2018-November 2022. The dominant side was defined pre-operatively using a tiered system based on laterality of highest biopsy Gleason Grade Group (GG), highest PIRADS lesion, number of lesions, and cancer volume. Univariable and multivariable logistic regression were performed for overall EPE, dominant side EPE, and non-dominant side EPE. Internal validation with leave one out and calibration curves were completed.
EPE was identified in 53% (317/601) of patients at RP. Side-specific factors (PIRADS, GG, abutment) were only associated with EPE on their respective side. Final variables in the model associated with EPE on the dominant and non-dominant sides included age, log PSA density (PSAD), side-specific PIRADS 5, side-specific GG3-5, and percentage positivity of systematic cores. AUCs for dominant and non-dominant side EPE were 0.77 (95% CI 0.73-0.80) and 0.79 (95% CI 0.74-0.84), respectively. MRI-identified abutment and prostate health index (PHI) did not improve model discrimination. Risk calculators available online at https://rossnm1.shinyapps.io/PredictionOfEPELaterality/ .
PSA, side-specific PIRADS, side-specific GG, and percentage positivity of systematic cores were associated with side-specific EPE at RP and incorporated into a risk calculator to assist in surgical planning and nerve-sparing decisions at time of RP.
传统的列线图可以提示前列腺外扩展（EPE）的存在，但不能提示其侧别，而侧别对于手术规划仍然很重要，并且传统列线图尚未充分纳入多参数MRI数据。我们评估了手术病理中侧别特异性EPE的预测因素，包括MRI特征，并开发了侧别特异性EPE风险计算器。
这是一项回顾性队列研究，研究对象为2018年7月至2022年11月在我们的11家医院医疗系统中接受根治性前列腺切除术（RP）前接受多参数MRI评估的患者。术前使用基于最高活检Gleason分级组（GG）的侧别、最高前列腺影像报告和数据系统（PIRADS）病变、病变数量和癌体积的分层系统来定义优势侧。对总体EPE、优势侧EPE和非优势侧EPE进行单变量和多变量逻辑回归分析。完成留一法内部验证和校准曲线分析。
在RP时，53%（317/601）的患者被发现有EPE。侧别特异性因素（PIRADS、GG、毗邻关系）仅与各自侧别的EPE相关。模型中与优势侧和非优势侧EPE相关的最终变量包括年龄、log PSA密度（PSAD）、侧别特异性PIRADS 5、侧别特异性GG3-5以及系统穿刺活检阳性率。优势侧和非优势侧EPE的曲线下面积（AUC）分别为0.77（95%可信区间0.73-0.80）和0.79（95%可信区间0.74-0.84）。MRI识别的毗邻关系和前列腺健康指数（PHI）并未改善模型的区分能力。风险计算器可在https://rossnm1.shinyapps.io/PredictionOfEPELaterality/在线获取。
PSA、侧别特异性PIRADS、侧别特异性GG以及系统穿刺活检阳性率与RP时的侧别特异性EPE相关，并被纳入风险计算器，以协助RP时的手术规划和保留神经的决策。
