提吉特
比例危险模型
单变量分析
医学
肿瘤科
内科学
生存分析
宫颈癌
单变量
癌症
多元分析
免疫疗法
多元统计
数学
统计
作者
Wenxue Zou,Rui Huang,Peihang Li,Xiang Liu,Qingyu Huang,Jinbo Yue,Chao Liu
标识
DOI:10.1016/j.jiph.2023.01.019
摘要
To investigate T cell immunoreceptor with Ig and ITIM domain (TIGIT), V-domain Ig suppressor of T cell activation (VISTA), and lymphocyte-activation gene-3 (LAG-3) expression in pathological tissue of human papillomavirus (HPV)-infected cervical cancer (CC) patients and their relationship with patient prognosis.Clinical data of 175 patients with HPV-infected CC were collected retrospectively. Tumor tissue sections were stained immunohistochemically for TIGIT, VISTA, and LAG-3. The Kaplan-Meier method calculated patient survival. Univariate and multivariate Cox proportional hazards models analyzed all potential risk factors for survival.When combined positive score (CPS)= 1 was used as the cut-off value, the Kaplan-Meier survival curve showed that the progression-free survival (PFS) and overall survival (OS) of patients with positive expression of TIGIT and VISTA are shorter (both p < 0.05). Univariate COX regression analysis showed that the positive expression of TIGIT and VISTA are related to patient PFS and OS (both HR>1.0 and p < 0.05). Multivariate COX regression analysis showed that TIGIT-positive patients had shorter OS and VISTA-positive patients had shorter PFS (both HR>1.0 and p < 0.05). There is no significant correlation between LAG-3 expression and PFS or OS. When CPS= 10 was used as the cut-off value, Kaplan-Meier survival curve showed that TIGIT-positive patients had shorter OS (p = 0.019). Univariate COX regression analysis showed that TIGIT-positive expression was associated with the OS of patients (HR=2.209, CI: 1.118-4.365, p = 0.023). However, multivariate COX regression analysis showed that TIGIT expression was not associated significantly with OS. There was no significant correlation between VISTA and LAG-3 expression and PFS or OS.TIGIT and VISTA are associated closely with HPV-infected CC prognosis and are effective biomarkers.
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