Tian Xiao-Peng, Ma Shu-Yun, Young Ken H, Ong Choon Kiat, Liu Yan-Hui, Li Zhi-Hua, Zhai Qiong-Li, Huang Hui-Qiang, Lin Tong-Yu, Li Zhi-Ming, Xia Zhong-Jun, Zhong Li-Ye, Rao Hui-Lan, Li Mei, Cai Jun, Zhang Yu-Chen, Zhang Fen, Su Ning, Li Peng-Fei, Zhu Feng, Xu-Monette Zijun Y, Wong Esther Kam Yin, Ha Jeslin Chian Hung, Khoo Lay Poh, Ai Le, Cheng Run-Fen, Lim Jing Quan, de Mel Sanjay, Ng Siok-Bian, Lim Soon Thye, Cai Qing-Qing
Department of Medical Oncology and.
State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Blood. 2021 Aug 12;138(6):452-463. doi: 10.1182/blood.2020010637.
Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP-based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP-based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P < .001). The 7-SNP-based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP-based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP-based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.
基于临床病理变量的现有预后评分系统，在预测接受非蒽环类药物治疗的结外自然杀伤/T细胞淋巴瘤（ENKTL）患者的生存和治疗反应方面存在不足。我们旨在构建一个基于单核苷酸多态性（SNP）的分类器，以提高预测准确性并指导临床决策。分析了来自国际中心的722例ENKTL患者的数据。在训练队列（n = 336）中使用LASSO Cox回归构建了基于7个SNP的分类器，并在内部测试队列（n = 144）和2个外部验证队列（n = 142和n = 100）中进一步验证。基于7个SNP的分类器在训练队列和3个验证队列中显示出良好的预后预测效能。通过该分类器计算出的高风险和低风险评分患者的无进展生存期（PFS）和总生存期（OS）存在显著差异（所有P <.001）。多因素分析进一步证明基于7个SNP的分类器是一个独立的预后因素，其预测准确性明显优于临床病理风险变量。基于7个SNP的分类器的应用不受样本类型的影响。值得注意的是，对于高危Ann Arbor I期患者，化疗联合放疗与单纯放疗相比，显著改善了PFS和OS，而低危患者的这两种治疗方式之间没有统计学差异。构建了一个包含该分类器和临床病理变量的列线图；它显示出比单独任何一个变量都明显更好的预测准确性。基于7个SNP的分类器是ENKTL现有风险分层系统的补充，这可能对ENKTL患者的临床决策具有重要意义。
