Risk Factors of Lung Cancer Patients: A Survival Analysis with R
Introduction: This paper studies risk factors which can have effects on the survival time of lung cancer patients during the treatment.
Methods: The Cox proportional-hazards model has been applied for investigating the association between the survival time of patients and the predictors such as age, gender, the weight of patients, meal, the ECOG, and Karnofsky scores.
Results: In the study, we find that the ECOG score, the Karnofsky score evaluated by doctors and the gender are the top three factors that significantly affect the hazard rate. Also, we utilize the estimated model to predict survival probability for the patients.
Conclusion: In this article, we intentionally present a complete and detailed guide on how to perform a R-based package in survival analysis step by step as well as how to interpret all output results