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

Abstract

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 breast cancer 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