Cimino Sebastiano, Reale Giulio, Castelli Tommaso, Favilla Vincenzo, Giardina Raimondo, Russo Giorgio Ivan, Privitera Salvatore, Morgia Giuseppe
a Urology Section, Department of Urology , University of Catania , Catania , Italy.
Scand J Urol. 2017 Oct;51(5):345-350. doi: 10.1080/21681805.2017.1332680. Epub 2017 Jun 23.
The aim of this study was to analyze the discriminative capabilities of Briganti, Partin and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms in predicting lymph-node invasion (LNI) and to perform a meta-analysis to yield pooled area under the receiver operating characteristics curves (AUCs) for model comparison.
An electronic search of the MEDLINE and Embase databases up to October 2016 was undertaken. The AUC value, total number of patients and rate of LNI were extracted from the included references. After excluding redundant literature, 19 studies were identified including 86,338 patients. The Briganti, Partin and MSKCC nomograms were validated in 6629, 69,681 and 10,028 patients, respectively.
The pooled AUCs for Briganti, Partin, and MSKCC nomograms were 0.793, 0.778 and 0.780, respectively. The Mantel-Haenszel-derived comparison of AUC values revealed no statistical differences of predictive capabilities for Briganti vs Partin (p = 0.23), Briganti vs MSKCC (p = 0.83) and Partin vs MSKCC (p = 0.26). The accuracy of Briganti, Partin and MSKCC models is statistically similar in predicting the presence of LNI. International guidelines could consider these findings by reporting similarities in the accuracy of these models.
The accuracy of Briganti, Partin and MSKCC was similar in predicting the presence of LNI. Based on these results, patients and clinicians may use any of these nomograms without significant advantages.
本研究旨在分析布里甘蒂(Briganti)、帕廷(Partin)和纪念斯隆凯特琳癌症中心(MSKCC)列线图在预测淋巴结侵犯(LNI)方面的鉴别能力,并进行荟萃分析以得出用于模型比较的受试者操作特征曲线下面积(AUC)的合并值。
对截至2016年10月的MEDLINE和Embase数据库进行电子检索。从纳入的参考文献中提取AUC值、患者总数和LNI发生率。在排除重复文献后,确定了19项研究,共86338例患者。布里甘蒂、帕廷和MSKCC列线图分别在6629例、69681例和10028例患者中得到验证。
布里甘蒂、帕廷和MSKCC列线图的合并AUC分别为0.793、0.778和0.780。基于Mantel-Haenszel法对AUC值的比较显示,布里甘蒂与帕廷(p = 0.23)、布里甘蒂与MSKCC(p = 0.83)以及帕廷与MSKCC(p = 0.26)之间在预测能力上无统计学差异。布里甘蒂、帕廷和MSKCC模型在预测LNI存在方面的准确性在统计学上相似。国际指南在报告这些模型准确性的相似性时可考虑这些发现。
布里甘蒂、帕廷和MSKCC在预测LNI存在方面的准确性相似。基于这些结果,患者和临床医生可以使用这些列线图中的任何一种,而不存在明显优势。