Venclovas Zilvinas, Muilwijk Tim, Matjosaitis Aivaras J, Jievaltas Mindaugas, Joniau Steven, Milonas Daimantas
Department of Urology, Lithuanian University of Health Sciences, Medical Academy, LT-44307 Kaunas, Lithuania.
Department of Urology, Leuven University Hospital, 3000 Leuven, Belgium.
J Clin Med. 2021 Mar 2;10(5):999. doi: 10.3390/jcm10050999.
: The aim of the study was to compare the performance of the 2012 Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms as a predictor for pelvic lymph node invasion (LNI) in men who underwent radical prostatectomy (RP) with pelvic lymph node dissection (PLND), to examine their performance and to analyse the therapeutic impact of using 7% nomogram cut-off. : The study cohort consisted of 807 men with clinically localised prostate cancer (PCa) who underwent open RP with PLND between 2001 and 2019. The area under the curve (AUC) of the receiver operator characteristic analysis was used to quantify the accuracy of the 2012 Briganti and MSKCC nomograms to predict LNI. Calibration plots were used to visualise over or underestimation by the models and a decision curve analysis (DCA) was performed to evaluate the net benefit associated with the used nomograms. : A total of 97 of 807 patients had LNI (12%). The AUC of 2012 Briganti and MSKCC nomogram was 80.6 and 79.2, respectively. For the Briganti nomogram using the cut-off value of 7% would lead to reduce PLND in 47% (379/807), while missing 3.96% (15/379) cases with LNI. For the MSKCC nomogram using the cut-off value of 7% a PLND would be omitted in 44.5% (359/807), while missing 3.62% (13/359) of cases with LNI. : Both analysed nomograms demonstrated high accuracy for prediction of LNI. Using a 7% nomogram cut-off would allow the avoidance up to 47% of PLNDs, while missing less than 4% of patients with LNI.
本研究的目的是比较2012年布里甘蒂（Briganti）和纪念斯隆凯特琳癌症中心（MSKCC）列线图作为接受根治性前列腺切除术（RP）并盆腔淋巴结清扫术（PLND）的男性盆腔淋巴结侵犯（LNI）预测指标的性能，检验其性能，并分析使用7%列线图临界值的治疗影响。本研究队列由807例2001年至2019年间接受开放性RP及PLND的临床局限性前列腺癌（PCa）男性组成。采用受试者操作特征分析的曲线下面积（AUC）来量化2012年布里甘蒂和MSKCC列线图预测LNI的准确性。校准图用于直观显示模型的高估或低估情况，并进行决策曲线分析（DCA）以评估所使用列线图的净效益。807例患者中共有97例发生LNI（12%）。2012年布里甘蒂和MSKCC列线图的AUC分别为80.6和79.2。对于布里甘蒂列线图，使用7%的临界值可使47%（379/807）的患者避免PLND，但会遗漏3.96%（15/379）的LNI病例。对于MSKCC列线图，使用7%的临界值可使44.5%（359/807）的患者避免PLND，但会遗漏3.62%（13/359）的LNI病例。两种分析的列线图在预测LNI方面均显示出较高的准确性。使用7%的列线图临界值可避免高达47%的PLND，同时遗漏LNI患者不到4%。
