Ahmad Reza Baghestani - Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Farid Zayeri
Mohammad Esmaeil Akbari
Leyla Shojaee

Introduction One of the malignant tumors is Breast Cancer (BC) that starts in the cells of breast. There is many model 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 ususal 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.

Breast Neoplasm, Cancer Research Center, Cure Rate Model, Deviance Information Criteria (DIC), Log normal, Survival Analysis