Oderda Marco, Diamand Romain, Albisinni Simone, Calleris Giorgio, Carbone Antonio, Falcone Marco, Fiard Gaelle, Gandaglia Giorgio, Marquis Alessandro, Marra Giancarlo, Parola Cinzia, Pastore Antonio, Peltier Alexandre, Ploussard Guillaume, Roumeguère Thierry, Sanchez-Salas Rafael, Simone Giuseppe, Smelzo Salvatore, Witt John H, Gontero Paolo
Division of Urology, Città della Salute e della Scienza, Molinette Hospital, University of Turin, Torino, Italy.
Urology Department, Hôpital Erasme, University Clinics of Brussels, Université Libre de Bruxelles, Brussels, Belgium.
BJU Int. 2021 Mar;127(3):318-325. doi: 10.1111/bju.15220. Epub 2020 Sep 19.
To externally validate the currently available nomograms for predicting lymph node invasion (LNI) in patients with prostate cancer (PCa) and to assess the potential risk of complications of extended pelvic lymph node dissection (ePLND) when using the recommended threshold.
A total of 14 921 patients, who underwent radical prostatectomy with ePLND at eight European tertiary referral centres, were retrospectively identified. After exclusion of patients with incomplete biopsy or pathological data, 12 009 were included. Of these, 609 had undergone multiparametic magnetic resonance imaging-targeted biopsies. Among ePLND-related complications we included lymphocele, lymphoedema, haemorrhage, infection and sepsis. The performances of the Memorial Sloan Kettering Cancer Centre (MSKCC), Briganti 2012, Briganti 2017, Briganti 2019, Partin 2016 and Yale models were evaluated using receiver-operating characteristic curve analysis (area under the curve [AUC]), calibration plots, and decision-curve analysis.
Overall, 1158 patients (9.6%) had LNI, with a mean of 17.7 and 3.2 resected and positive nodes, respectively. No significant differences in AUCs were observed between the MSKCC (0.79), Briganti 2012 (0.79), Partin 2016 (0.78), Yale (0.80), Briganti 2017 (0.81) and Briganti 2019 (0.76) models. A direct comparison of older models showed that better discrimination was achieved with the MSKCC and Briganti 2012 nomograms. A tendency for underestimation was seen for all the older models, whereas the Briganti 2017 and 2019 nomograms tended to overestimate LNI risk. Decision-curve analysis showed a net benefit for all models, with a lower net benefit for the Partin 2016 and Briganti 2019 models. ePLND-related complications were experienced by 1027 patients (8.9%), and 12.6% of patients with pN1 disease.
The currently available nomograms have similar performances and limitations in the prediction of LNI. Miscalibration was present, however, for all nomograms showing a net benefit. In patients with only systematic biopsy, the MSKCC and Briganti 2012 nomograms were superior in the prediction of LNI.
对外验证目前可用的预测前列腺癌(PCa)患者淋巴结侵犯(LNI)的列线图,并评估使用推荐阈值时扩大盆腔淋巴结清扫术(ePLND)的潜在并发症风险。
回顾性纳入了在8个欧洲三级转诊中心接受根治性前列腺切除术及ePLND的14921例患者。排除活检或病理数据不完整的患者后,纳入12009例。其中,609例接受了多参数磁共振成像靶向活检。ePLND相关并发症包括淋巴囊肿、淋巴水肿、出血、感染和脓毒症。使用受试者操作特征曲线分析(曲线下面积[AUC])、校准图和决策曲线分析评估纪念斯隆凯特琳癌症中心(MSKCC)、布里甘蒂2012、布里甘蒂2017、布里甘蒂2019、帕廷2016和耶鲁模型的性能。
总体而言,1158例患者(9.6%)发生LNI,平均切除淋巴结数和阳性淋巴结数分别为17.7个和3.2个。MSKCC模型(0.79)、布里甘蒂2012模型(0.79)、帕廷2016模型(0.78)、耶鲁模型(0.80)、布里甘蒂2017模型(0.81)和布里甘蒂2019模型(0.76)的AUCs无显著差异。对较旧模型的直接比较表明,MSKCC和布里甘蒂2012列线图具有更好的区分能力。所有较旧模型均有低估趋势,而布里甘蒂2017和2019列线图倾向于高估LNI风险。决策曲线分析显示所有模型均有净获益,帕廷2016和布里甘蒂2019模型的净获益较低。1027例患者(8.9%)发生了ePLND相关并发症,pN1疾病患者的发生率为12.6%。
目前可用的列线图在预测LNI方面具有相似的性能和局限性。然而,所有显示有净获益的列线图均存在校准错误。在仅进行系统活检的患者中,MSKCC和布里甘蒂2012列线图在预测LNI方面更具优势。