首页/数据集/Multivariate Cox regression analysis for disease-free survival in TCGA-ESCA.

Multivariate Cox regression analysis for disease-free survival in TCGA-ESCA.

Figshare2025-06-26 更新2026-04-28 收录

数据链接：

https://figshare.com/articles/dataset/Multivariate_Cox_regression_analysis_for_disease-free_survival_in_TCGA-ESCA_/29420292 数据链接链接失效反馈

官方服务：

资源简介：

Multivariate Cox regression analysis for disease-free survival in TCGA-ESCA.

应用场景：

创建时间：

2025-06-26

癌症预后基因标记

消化系统肿瘤生存分析

*Adjusted for age, gender, stage, op and CCRT status. #with 2 missing values. ADD: additive; DOM: dominant; REC, recessive; MAF: minor allele frequency.

NIAID Data Ecosystem40

Results of the multivariate Cox regression analysis for cholangiocarcinoma (CCA) patients’ survival.

消化系统肿瘤生存分析

预后预测

Results of the multivariate Cox regression analysis for cholangiocarcinoma (CCA) patients’ survival.

NIAID Data Ecosystem30

Table_1_Survival Status of Esophageal Cancer Patients and its Determinants in Ethiopia: A Facility Based Retrospective Cohort Study.docx

消化系统肿瘤生存分析

化疗疗效评估

BackgroundGlobally, the incidence and mortality due to esophageal cancer are increasing, particularly in low- and middle-income countries. Cancer of the esophagus is the eighth in incidence and sevent

NIAID Data Ecosystem10

Cox Regression Survival Analysis.

消化系统肿瘤生存分析

预后因素研究

1In pack year. 2At time of esophagectomy. 3History of Barrett's Esophagus. 4High risk group determined by adjacent squamous epithelial tissue mean Survivin levels. 5High risk group determined by tumor

NIAID Data Ecosystem40

Data_Sheet_1_Prognostic Value of an Inflammation-Related Index in 6,865 Chinese Patients With Postoperative Digestive Tract Cancers: The FIESTA Study.PDF

肿瘤预后生物标志物

消化系统肿瘤生存分析

Objectives: We sought to determine the optimal cutting points for two inflammatory biomarkers, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), to assess their prognostic

NIAID Data Ecosystem20

Multivariate Cox regression analysis for disease-free survival in TCGA-ESCA.

资源简介：

相关数据集