The evaluation of Cox and Weibull proportional hazards models and their applications to identify factors influencing survival time in acute leukemia

AUTHORS

Saeed Hosseini Teshnizi 1 , * , Shahram Zare 2 , Mehdi Tazhibi 3

1 Instructor Of Biostatistics of Premedical, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.

2 Associate Professor Department of Community Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.

3 Assistant Professor Department of Biostatistics & Epidemiology, Isfahan University of Medical Sciences, Isfahan, Iran.

How to Cite: Hosseini Teshnizi S, Zare S , Tazhibi M. The evaluation of Cox and Weibull proportional hazards models and their applications to identify factors influencing survival time in acute leukemia, Hormozgan Med J. 2012 ; 15(4):e88497.

ARTICLE INFORMATION

Hormozgan Medical Journal: 15 (4); e88497
Published Online: August 01, 2011
Article Type: Research Article
Received: July 31, 2010
Accepted: August 01, 2011

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Abstract

Introduction: The most important models used in analysis of survival data is proportional
hazards models. Applying this model requires establishment of the relevance proportional
hazards assumption, otherwise it world lead to incorrect inference. This study aims to
evaluate Cox and Weibull models which are used in identification of effective factors on
survival time in acute leukemia.
Methods: In a retrospective study the information on 197 patients with acute leukemia
were collected. The proportional hazards models were used to identify effective factors on
survival time. Goodness-of-fit test and two graphical procedures based on the scaled
Schoenfeld residuals were used to evaluate the proportional hazards assumption of the Cox
and Weibull models. Finally, to assess the accuracy of fitted models, Martingel residuals
graphic method was applied for goodness of fit investigation. S-plus statistical package was
used for analysis.
Results: The results showed that the assumptions of proportional hazards for Cox and
Weibull models are correct. Based on the models, variables such as, age, residence place,
and WBC, showed significant effect on survival time (P<0.05). Finally, AIC criteria
showed that Cox semi- parametric model had better fit on the survival data of the patients
with acute leukemia.
Conclusion: Assessing the Cox-snell and Martingel residuals plots showed that Cox model
is more efficient than Weibull model for the survival time of the patients with acute
leukemia. Significance of WBC factor in the model, indicate that control of this factor is
effective in increasing patients' survival.

Keywords

Leukemia - Proportional Hazards Models - Survival

© 2012, Hormozgan Medical Journal. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

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