Comparison Cure Rate Models by DIC Criteria in Breast Cancer Data

Baghestani, Ahmad Reza; Shahmirzalou, Parviz; Sayad, Soheila; Akbari, Mohammad Esmaeil; Zayeri, Farid

doi:10.22034/APJCP.2018.19.6.1601

Comparison Cure Rate Models by DIC Criteria in Breast Cancer Data

Document Type : Research Articles

Authors

¹ Physiotherapy Research Centre ,Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

² Social Determinants of Health Research Center, Yasuj University of Medical Sciences, Yasuj, Iran.

³ Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

⁴ Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

10.22034/APJCP.2018.19.6.1601

Abstract

Background: One of the malignant tumors is Breast Cancer (BC) that starts in the cells of breast. There is many
models for survival analysis of patients such as Cox PH model, Parametric models etc. But some disease are that
all of patients will not experience main event then usual survival model is inappropriate. In addition, In the presence of
cured patients, if researcher can specify distribution of survival time, usually cure rate models are preferable to
parametric models. Distribution of Survival time can be Weibull, Log normal, Logistic, Gamma and so. Comparison of
Weibull, Log normal and Logistic distribution for finding the best distribution of survival time is purpose of this study.
Material and Methods: Among 787 patients with BC by Cancer Research Center recognized and followed from
1985 until 2013. Variables stage of cancer, age at diagnosis, tumor size and Number of Removed Positive Lymph
Nodes (NRPLN) for fitting Cure rate model were selected. The best model selected with DIC criteria. All analysis
were performed using SAS 9.2. Results: Mean (SD) of age was 48.47 (11.49) years and Mean of survival time and
Maximum follow up time was 326 and 55.12 months respectively. During following patients, 145 (18.4%) patients
died from BC and others survived (censored). Also, 1-year, 5-year and 10-year survival rate was 94, 77 and 56 percent
respectively. Log normal model with smaller DIC were selected and fitted. All of mentioned variables in the model
were significant on cure rate. Conclusion: This study indicated that survival time of BC followed from Log normal
distribution in the best way.

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