Study
            
                PLCO
                (Learn more about this study)
            
 
            
            
                Project ID
                
                    
                        PLCO-1434
                    
                
            
            
                Initial CDAS Request Approval
                Jan 4, 2024
            
            Title
            Statistical Modeling on Lung Cancer
            
                Summary
                We aim to apply advanced statistical methodologies to discern the prominent factors and their interactions influencing lung cancer. Our objective includes constructing a statistical model for lung cancer tumor size, emphasizing key risk factors and their interactions. Subsequently, we will prioritize these factors and interactions based on their impact on lung cancer tumor size. Additionally, we plan to conduct both parametric and non-parametric analyses of the survival time for lung cancer, considering variables such as ethnicity, gender, and cancer stage. This analysis will yield survival functions, providing valuable insights into the dynamics of lung cancer survival across different demographic and clinical categories.
            
            
                Aims
                1. Employing advanced statistical methods, we aim to pinpoint individual risk factors and their interactions for constructing a comprehensive statistical model of lung cancer tumor size.
2. Following identification, we will rank the risk factors and interaction terms based on their respective contributions to lung cancer.
Collaborators
                
                Dr. Chris P. Tsokos (Distinguished University Professor of University of South Florida), ctsokos@usf.edu