SURVIVAL ANALYSIS OF CHRONIC KIDNEY FAILURE PATIENTS USING THE COX STRATIFIED MODEL AND RANDOM SURVIVAL FOREST

DOI: https://doi.org/10.30598/barekengvol20iss2pp1527–1540
Keywords: Survival Analysis, Chronic Kidney Failure, Cox Stratified Model, Random Survival Forest, Mortality, Hemodialysis

Abstract

This study aims to analyze the factors influencing the survival of chronic kidney failure patients undergoing hemodialysis and to compare the performance of the Cox Stratified Model with the Random Survival Forest (RSF) using retrospective data from 741 patients at Asy-Syifa General Hospital, Indonesia. Data were analyzed using the Cox Stratified Model to address violations of the proportional hazards assumption and RSF to capture non-linear patterns and complex interactions among variables. The results showed that age, hypertension, diabetes, anemia, and hemodialysis frequency significantly affected survival, with a C-Index of 0.66 for the Cox Stratified Model and 0.6558 for RSF. The limitations of this study include its single-center retrospective design, which may limit generalizability, potential residual confounding from unmeasured variables, as well as the interpretability limitations and higher computational demands of RSF. The originality of this research lies in the direct comparison between advanced statistical models and machine learning methods in a cohort of chronic kidney failure patients in Indonesia, providing new insights for improving risk stratification and clinical prediction.

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Published
2026-01-26
How to Cite
[1]
A. L. P. Hamid, B. Susetyo, and A. Kurnia, “SURVIVAL ANALYSIS OF CHRONIC KIDNEY FAILURE PATIENTS USING THE COX STRATIFIED MODEL AND RANDOM SURVIVAL FOREST”, BAREKENG: J. Math. & App., vol. 20, no. 2, pp. 1527–1540, Jan. 2026.
Issue
Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2026 Assyifa Lala Pratiwi Hamid, Budi Susetyo, Anang Kurnia

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