Please use this identifier to cite or link to this item: https://doi.org/10.1182/blood.2020010637
Title: A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma
Authors: 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
Keywords: Science & Technology
Life Sciences & Biomedicine
Hematology
NASAL-TYPE
BIOMARKER
MODEL
Issue Date: 12-Aug-2021
Publisher: AMER SOC HEMATOLOGY
Citation: 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 (2021-08-12). A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma. BLOOD 138 (6) : 452-463. ScholarBank@NUS Repository. https://doi.org/10.1182/blood.2020010637
Abstract: 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.
Source Title: BLOOD
URI: https://scholarbank.nus.edu.sg/handle/10635/206596
ISSN: 00064971
15280020
DOI: 10.1182/blood.2020010637
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