Prognostic factors of metastases in breast cancer patients using the recurrent Andersen-Gill model

Introduction: Identifying the risk factors in the treatment of metastatic breast cancer patients is a major concern. The aim of this study was to determine prognostic factors for metastasis of breast cancer using a regression model for recurrent data. Materials and Methods: The data used in the study were for the records of 133 women with breastcancer who underwent surgery and treatment at hospital Fayazbakhsh during 2005- 2007. Patients were followed until 2011 April and their final situations recorded. To determine the prognostic factors, a univariate Andersen-Gill model were fitted. Significant factors at univariate model were entered in multiple AG model. Results: During 5833 person-month follow up of patients, 25 patients(18.8%) died and 108 patients(81.2%) were alive. The first metastasis mostly shown in brain and liver (5.3%) and the second one in brain(3.8%). In univariate analysis, grade, Her2 and LNR were shown as prognostic factors for metastasis of breast cancer in multiple analysis model (P<0.05). Conclusion: Creating breast cancer screening and knowledge of women about the importance of periodic checkups and early diagnosis is an important factor for the cure and prevention of metastasis of tumors among breast cancer patients.