Basic Theory and Methodology
Choice and application of time scale selection for Cox proportional hazards regression model in cohort studies
Zhuoying Li, Qiuming Shen, Jiayi Tuo, Dandan Tang, Yuxuan Xiao, Longgang Zhao, Yongbing Xiang
Published 2022-12-10
Cite as Chin J Epidemiol, 2022, 43(12): 2002-2007. DOI: 10.3760/cma.j.cn112338-20220720-00644
Abstract
Cox proportional hazards regression model (Cox model) is the most commonly used multivariate approach in time-to-event data analysis. A vital issue in fitting Cox model is choosing the appropriate time scale related to the occurrence of the outcome events. However, few domestic studies have focused on selecting and applying time scales for Cox model in the analysis of cohort study data. This study briefly introduced and compared several time scales in the reports from literature; and used data from the Shanghai Women's Health Study to illustrate the impact of different time scales on data analysis results, using the association between central obesity and the risk of liver cancer as an example. On this basis, several suggestions on selecting time scales in Cox model are proposed to provide a reference for the analysis of cohort study data.
Key words:
Cohort study; Cox proportional hazards regression model; Risk factor; Time scale
Contributor Information
Zhuoying Li
School of Public Health, Fudan University, Shanghai 200032, China
State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China
Qiuming Shen
State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China
Jiayi Tuo
State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China
Dandan Tang
State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China
Yuxuan Xiao
State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China
Longgang Zhao
Department of Epidemiology &
Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia 29201, USA
Yongbing Xiang
State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China
