- Volume 14 Issue 11
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Comparison between Parametric and Semi-parametric Cox Models in Modeling Transition Rates of a Multi-state Model: Application in Patients with Gastric Cancer Undergoing Surgery at the Iran Cancer Institute
- Zare, Ali (Department of Epidemiology and Biostatistics, University of Medical Sciences) ;
- Mahmoodi, Mahmood (Department of Epidemiology and Biostatistics, University of Medical Sciences) ;
- Mohammad, Kazem (Department of Epidemiology and Biostatistics, University of Medical Sciences) ;
- Zeraati, Hojjat (Department of Epidemiology and Biostatistics, University of Medical Sciences) ;
- Hosseini, Mostafa (Department of Epidemiology and Biostatistics, University of Medical Sciences) ;
- Naieni, Kourosh Holakouie (Department of Epidemiology and Biostatistics, University of Medical Sciences)
- Published : 2013.11.30
Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses. Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state
Gastric cancer;multi-state model;parametric model;proportional hazards model;transition rate
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