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Background: The analysis of disease-free survival and related factors leads to a better understanding of the patient’s condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model. Methods: This retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer. Results: Disease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment ( P value 5 cm were 31.06 and 27 months less than patients with the tumor size

Background: Using data from different health centers can provide more accurate knowledge of the survival prognostic factors and their effect on the patient’s survival. In this multicenter study, we aimed to investigate the role of prognostic factors on breast cancer survival with large data set. Methods: This historical cohort study was carried out using data from 1785 participants with breast cancer. Data were gathered from medical records of patients referring to 4 breast cancer research centers in Tehran, Iran, between 1997 and 2013. Age at diagnosis (year), size of the tumor, involve lymph nodes, tumor grade, type of surgery, auxiliary treatment of chemotherapy, radiotherapy, recurrence, and metastasis were the prognosis factors considered in this study. A shared frailty model with a gamma distribution for frailty term was used. Results: The median follow-up period was 29.71 months with the interquartile range of 19 to 61 months. During the follow-up period, 337 (18.9%) patients died from breast cancer and 1448 (81.1%) survived. The 1-, 3-, 5-, and 10-year survival rates were 96%, 84%, 76%, and 58%, respectively. In the Cox model by centers, in Center A, the type of surgery, number of nodes involved, and the grade 3 tumor; in center B, age, radiotherapy, metastasis, and between 1 and 3 involved nodes; in center C, age, radiotherapy, recurrence, metastasis, tumor size, and grade 3 tumor; and in center D, chemotherapy, metastasis, and lymph nodes involved were significant. Shared frailty model showed that type of surgery, number of lymph nodes involved, metastasis, radiotherapy, and the tumor grade are the prognostic factors survival in breast cancer. The frailty variance was significant, and it affirmed there was significant variability between centers. Conclusions: This study showed it is necessary to consider the frailty term in modeling multicenter survival studies and confirmed the importance of early diagnosis of cancer before the involvement of lymph nodes and the onset of metastasis and timely treatment could lead to longer life and increased quality of life for patients.

Objective: Bone is the most common site of metastasis in breast cancer. Prognostic factors for predicting bone metastases in breast cancer are controversial yet. In this study, we investigated clinical factors associated with secondary bone metastasis of breast cancer. Methods: In total, 1690 patients with breast cancer recorded between 2002 and 2012 in Motamed Cancer Institute, Tehran, Iran entered in the retrospective study. We studied age, menopausal status, histologic type, tumor size, number of cancerous axillary lymph nodes, serum concentrations of alkaline phosphatase (ALP), carcinogenicity antigen (CEA), cancer antigen (CA)-153, and hemoglobin (HB) in 2 groups with bone metastases (n = 123) and without it, respectively. We applied logistic regression to identify bone metastasis prognostic factors in breast cancer patients and calculated the cut-off value, sensitivity, and characteristics of independent prognostic factors using receiver operating characteristic (ROC) curve analysis. Results: Menopause, larger tumor size, and the greater number of cancerous axillary lymph nodes increased the chance of bone metastases significantly ( P .05). Logistic regression showed that age (odds ratio (OR) = 1.021), menopausal status (OR = 1.854), number of cancerous axillary lymph nodes (OR = 1.065), a tumor size between 2 and 5 cm diameter (OR = 2.002) and more than 5 cm diameter (OR = 4.009), and ALP (OR = 1.005) are independent prognostic factors associated with bone metastases. The ROC curve showed that the abovementioned factors have comparable predictive accuracy for bone metastases. Conclusions: Age, menopausal status, number of axillary lymph node metastases, tumor size, and ALP were identified as prognostic factors for bone metastasis in patients with breast cancer. So patients with these characteristics should be monitored more precisely with regular follow-ups.