Department of Urology, Institute of Medical Informatics and Biomathematics, University Hospital of Muenster, Muenster, Germany.
J Immunother. 2011 Mar;34(2):196-201. doi: 10.1097/CJI.0b013e3182027748.
A number of new agents have been approved for systemic therapy of metastatic renal cell carcinoma (mRCC) recently. Thereby, prognostic factors may aid in predicting the effectiveness of various treatment modalities in individual cases. Aim of this study was to determine the value of human leukocyte antigen (HLA) class II characteristics in predicting response of mRCC to combined immunochemotherapy (ICT). A retrospective study of 29 patients with mRCC treated with ICT was performed: 17 patients (group A) with long-term remission and 12 (group B) with progressive disease after ICT. DNA was used for high resolution typing of HLA-DRB1, -DRB3, -DRB4, -DRB5, -DQA1, and -DQB1. Statistical evaluation started with Classification and Regression Trees analysis. The assignment of single alleles to the groups was then aggregated to create a classification on a patients' basis. Finally, the accuracy of this test algorithm was evaluated. HLA-DRB1 (DRB1030104010402040711011501=progression) was the strongest discriminator between the 2 groups. The test algorithm defined all patients with at least one of these DRB1 alleles to be progressive after ICT. Thus, 12 of 12 patients of group B could have been identified as progressive (sensitivity=100%). However, only 10 of 17 patients of group A would have been identified as responding (specificity=58%). Thus, the test had a positive and negative predictive value of 63% and 100%, respectively. Approximately 5% to 10% of all patients with mRCC are able to benefit from ICT with long-term remission. HLA class II characteristics may aid in identifying this small subgroup of patients with mRCC.
最近,一些新的药物已被批准用于转移性肾细胞癌(mRCC)的系统治疗。因此,预后因素可能有助于预测各种治疗方法在个体病例中的有效性。本研究旨在确定人类白细胞抗原(HLA)Ⅱ类特征在预测 mRCC 对联合免疫化疗(ICT)反应中的价值。对 29 例接受 ICT 治疗的 mRCC 患者进行了回顾性研究:17 例(A 组)长期缓解,12 例(B 组)ICT 后疾病进展。使用 DNA 对 HLA-DRB1、-DRB3、-DRB4、-DRB5、-DQA1 和 -DQB1 进行高分辨率分型。统计评估从分类和回归树分析开始。然后将单个等位基因分配给组,以创建基于患者的分类。最后,评估了该测试算法的准确性。HLA-DRB1(DRB1030104010402040711011501=进展)是两组之间最强的区分因素。测试算法将至少具有这些 DRB1 等位基因之一的所有患者定义为 ICT 后进展。因此,B 组的 12 例患者均被识别为进展(敏感性=100%)。然而,A 组的 17 例患者中只有 10 例被识别为有反应(特异性=58%)。因此,该测试的阳性预测值和阴性预测值分别为 63%和 100%。大约 5%至 10%的 mRCC 患者能够从长期缓解的 ICT 中获益。HLA Ⅱ类特征可能有助于识别 mRCC 的这一小亚组患者。