Articles

Survey of Patients with Cervical Cancer in Hospital UniversitiSains Malaysia: Survival Data Analysis with Time-Dependent Covariate

Abstract

Cervical cancer is the third most common cancer among women in Malaysia. The objective of this study was to estimate the effect of explanatory variables on survival time of cervical cancer patients receiving treatment at a hospital in Malaysia.In this retrospective record review study, cervical cancer data obtained from Hospital UniversitiSains Malaysia (HUSM) was analysed. The data comprises of 120 patients who had been diagnosed as cervical cancer between 1(st) July 1995 and 30(th) June 2007, and obtained treatment from the hospital. The outcome variable was survival time (in months) from cervical cancer diagnosis to death. A stratified Weibull model was applied to study the effect of explanatory variable on survival time when there was time-dependent covariate in the model.Stage of disease and metastases were important prognostic variables. However, metastasis had been stratified because this variable did not satisfy the proportional hazard assumption. In without metastasis stratum, patients who were diagnosed at stage III & IV are at 2.30 times the risk of death as those in stage I & II. Meanwhile, in with metastasis stratum, patients in stage III & IV group had 3.53 times the hazard faced by patients in stage I & II.The prognosis of cervical cancer patients was dependent upon the stage at diagnosis, after the stratification of the metastasis variable. A poorer prognosis on survival was observed for patients in stage III & IV than those in stage I & II.

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IssueVol 42 No 9 (2013) QRcode
SectionArticles
Keywords
Cervical cancer Prognostic factor Survival Time-dependent covariate Weibull

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
1.
Juhan N, Abd Razak N, Zubairi YZ, Khattak MN, Naing NN. Survey of Patients with Cervical Cancer in Hospital UniversitiSains Malaysia: Survival Data Analysis with Time-Dependent Covariate. Iran J Public Health. 1;42(9):980-987.