Department of Urology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Department of Radiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Ann Surg Oncol. 2024 Nov;31(12):8405-8420. doi: 10.1245/s10434-024-15769-w. Epub 2024 Jul 30.
Due to the deep location of the prostate within the pelvic cavity, procedures of robot-assisted radical prostatectomy (RARP) might be challenged by the prostate size and the limited pelvic cavity space. This study aimed to investigate the roles of bony pelvic and prostate dimensions in RARP procedures by an original study coupled with a meta-analysis.
In the original study, patients undergoing multiport RARP between 2021 and 2022 were consecutively assessed. The associations of anatomic features with operative time (OT), estimated blood loss (EBL), and positive surgical margin (PSM) were evaluated using linear and logistic regression analyses as well as restricted cubic spline (RCS) analysis. Based on machine-learning algorithms, this study established predictive models for surgical difficulty and interpreted the model using SHapley Additive exPlanation (SHAP). In the meta-analysis, three databases were searched for eligible studies. Quantitative syntheses were subsequently performed.
Overall, 219 patients were enrolled in the original study. Prostate volume (PV) and the prostate volume-to-pelvic cavity index (PCI) ratio (PV-to-PCI ratio) were significantly associated with longer OT (P < 0.05). In the RCS models, U-shaped associations were observed between the prostate anteroposterior diameter (PAD) and OT, and between the prostate height (PH) and EBL, and an L-shaped association was observed between the anteroposterior diameter of the pelvic inlet (API) and EBL. The XGBoost model was superior to the logistic regression model in predicting prolonged OT. The meta-analysis demonstrated that greater PV was significantly associated with longer OT (β = 0.20; 95% confidence interval [CI] 0.12-0.27; odds ratio [OR] = 1.05; 95% CI 1.00-1.11), and a smaller PV could increase the risk of PSM (OR = 0.82; 95% CI 0.77-0.88).
A large prostate within a narrow and deep pelvis might suggest increased surgical difficulty of RARP. The size of the pelvic inlet also had a great impact on RARP. For PAD and PH, there seemed to be an optimal range with the lowest surgical difficulty. Machine-learning models based on the XGBoost algorithm could be successfully applied to predict the surgical difficulty of RARP.
由于前列腺位于盆腔深处，机器人辅助根治性前列腺切除术（RARP）的手术可能会受到前列腺大小和有限的盆腔空间的影响。本研究旨在通过原始研究和荟萃分析探讨骨盆和前列腺尺寸在 RARP 手术中的作用。
在原始研究中，连续评估了 2021 年至 2022 年间接受多端口 RARP 的患者。使用线性和逻辑回归分析以及受限立方样条（RCS）分析评估解剖特征与手术时间（OT）、估计失血量（EBL）和阳性手术切缘（PSM）的关系。基于机器学习算法，本研究建立了手术难度预测模型，并使用 Shapley Additive exPlanation（SHAP）对模型进行了解释。在荟萃分析中，检索了三个数据库以确定符合条件的研究。随后进行了定量综合分析。
共有 219 名患者纳入原始研究。前列腺体积（PV）和前列腺体积与骨盆腔指数（PCI）的比值（PV-to-PCI 比值）与 OT 延长显著相关（P < 0.05）。在 RCS 模型中，前列腺前后径（PAD）与 OT 之间以及前列腺高度（PH）与 EBL 之间呈 U 型关系，骨盆入口前后径（API）与 EBL 之间呈 L 型关系。XGBoost 模型在预测 OT 延长方面优于逻辑回归模型。荟萃分析表明，较大的 PV 与较长的 OT 显著相关（β=0.20；95%置信区间[CI]0.12-0.27；比值比[OR]1.05；95%CI 1.00-1.11），较小的 PV 可增加 PSM 的风险（OR=0.82；95%CI 0.77-0.88）。
在狭窄而深的骨盆中存在大的前列腺可能表明 RARP 的手术难度增加。骨盆入口的大小对 RARP 也有很大的影响。对于 PAD 和 PH，似乎存在一个最佳范围，手术难度最低。基于 XGBoost 算法的机器学习模型可以成功应用于预测 RARP 的手术难度。
