ANALISIS MODEL REGRESI COX PROPORTIONAL HAZARD PADA STUDI KASUS PASIEN KANKER PARU-PARU
Keywords:
Lung Cancer, Survival Analysis, Cox Proportional Hazard
Abstract
The high mortality rate caused by lung cancer is at an alarming rate. Lung cancer patients must be treated quickly and appropriately. One method often used in survival analysis is the cox proportional hazard regression model. In the cox proportional hazard regression model, the independent variables used must meet the proportional hazard assumption. The results showed that the variables that had a significant effect on the Cox Proportional Hazard regression analysis using a 90% confidence level in the survival time of lung cancer patients were cell type 2, cell type 3 and performance status. Meanwhile, other variables namely treatment, cell type 1, disease duration, age, and prior therapy did not significantly influence.
References
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Kleibaum, D.G & Klein, M., (2005), Survival Analysis: A Self-Learning Text, Second Edition. New York, Springer.
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Cox, D. R., (1972), Regression Model and Life Table. J Roy Stat Soc B, 34, 187- 202.
Kleibaum, D.G & Klein, M., (2005), Survival Analysis: A Self-Learning Text, Second Edition. New York, Springer.
Le, C. T., (1997), Applied Survival Analysis. New York, John Wiley and Sons, Inc.
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