Development of Individual Survival Estimating Program for Cancer Patients’ Management
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Objectives: The goal of this report is to present an individual patient’s survival estimation curve using the each institution’s survival data after Cox proportional hazard analysis. Methods: The program was developed in three parts: input of basic data from Cox proportional hazard analysis, input of individual patient’s covariates, and presentation of individual patient’s survival curve. In the first part, the average survival rates with each survival time were entered as the means of covariates using the results of Cox proportional hazard analysis. In the second part, the individual patient’s values of each covariate were entered for the calculation of survival estimation. In the third part, the survival curve was displayed according to the input data. Results: The data of 2,652 breast cancer patients were analyzed. Cox regression analysis was conducted using the covariates of age, tumor size, N stage, and M stage. The individual patient’s survival curve was presented using the basic data and covariate factors. In the breast cancer patients, the program presented survival curves according to each patient’s age, tumor size, N stage, and M stage. The data of 251 thyroid cancer patients were analyzed by a similar method. Conclusions: We developed a program to present individual survival curves of cancer patients. This program will be useful for clinicians to assist their decision-making and discussion with patients.
Abstract
Objectives: The goal of this report is to present an individual patient’s survival estimation curve using the each institution’s survival data after Cox proportional hazard analysis. Methods: The program was developed in three parts: input of basic data from Cox proportional hazard analysis, input of individual patient’s covariates, and presentation of individual patient’s survival curve. In the first part, the average survival rates with each survival time were entered as the means of covariates using the results of Cox proportional hazard analysis. In the second part, the individual patient’s values of each covariate were entered for the calculation of survival estimation. In the third part, the survival curve was displayed according to the input data. Results: The data of 2,652 breast cancer patients were analyzed. Cox regression analysis was conducted using the covariates of age, tumor size, N stage, and M stage. The individual patient’s survival curve was presented using the basic data and covariate factors. In the breast cancer patients, the program presented survival curves according to each patient’s age, tumor size, N stage, and M stage. The data of 251 thyroid cancer patients were analyzed by a similar method. Conclusions: We developed a program to present individual survival curves of cancer patients. This program will be useful for clinicians to assist their decision-making and discussion with patients.
참고문헌 (9)
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