Application of the Cox Proportional Hazard Model on Survival Data of Multiple Myeloma Patients Using the R Application

Multiple Myeloma is a type of blood cancer characterized by the proliferation of malignant plasma cells in the bone marrow and can affect the patient's survival. This study aims to analyze the influence of age, sex, and protein levels on patient survival time. Multiple Myeloma uses the Cox Proportional Hazards model. The data used came from 47 patients with variables of survival time, patient status (dead or alive), age, gender, and protein content. The analysis was carried out using R software. The model match test with the likelihood ratio test also showed insignificant results, but testing of the assumption of proportional hazards through residual Schoenfeld showed that all variables met the model's assumptions. Thus, the Cox PH model in this study is technically valid, but its predictive power is still limited, so further model development is recommended by increasing the amount of data or considering other more relevant variables.

Authors

Institutions

Publication Details

Journal
Indonesian Council of Premier Statistical Science.
Published
2025-08-30
DOI
https://doi.org/10.24014/icopss.v4i2.37880
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of the Cox Proportional Hazard Model on Survival Data of Multiple Myeloma Patients Using the R Application

Surya Nengsih, Achmad Riyan
Indonesian Council of Premier Statistical Science.
Statistical Distribution Estimation and Applications
article

Application of the Cox Proportional Hazard Model on Survival Data of Multiple Myeloma Patients Using the R Application

Surya Nengsih, Achmad Riyan
article en

Abstract

Multiple Myeloma is a type of blood cancer characterized by the proliferation of malignant plasma cells in the bone marrow and can affect the patient's survival. This study aims to analyze the influence of age, sex, and protein levels on patient survival time. Multiple Myeloma uses the Cox Proportional Hazards model. The data used came from 47 patients with variables of survival time, patient status (dead or alive), age, gender, and protein content. The analysis was carried out using R software. The model match test with the likelihood ratio test also showed insignificant results, but testing of the assumption of proportional hazards through residual Schoenfeld showed that all variables met the model's assumptions. Thus, the Cox PH model in this study is technically valid, but its predictive power is still limited, so further model development is recommended by increasing the amount of data or considering other more relevant variables.

Indonesian Council of Premier Statistical Science.Vol. 4(2)
Universitas Islam Negeri Sultan Syarif Kasim Riau (ID)
Openalex Percentile: Top 75%
Statistical Distribution Estimation and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Application of the Cox Proportional Hazard Model on Survival Data of Multiple Myeloma Patients Using the R Application — Surya Nengsih, Achmad Riyan · Indonesian Council of Premier Statistical Science. (2025) | TGRS Research Map | TGRS