Survival analysis in breast cancer

Aim: The aim of this study is to make an application of retrospective survival analysis method in breast cancer patients. Material and Method: The data of 334 breast cancer patients treated at Dicle University Oncology Hospital between 2017 and 2018 were used in the study. The variables that have an effect on the survival of the patient were tried to be determined. Median, mean survival and the effects of factors were compared with three different treatment methods. The data obtained were analyzed by Survival Tables, Kaplan-Meier and Cox Regression method of survival analysis. Results: Of the 334 patients included in the study, 5,7% (19) died while 94,3% (315) were alive. 99,4% (332) of the patients were female and 0,6% (2) were male. There is not enough information about 1,5% of the patients (5). In the analysis performed according to the three methods of survival analysis, there was no significant difference in survival compared to lymph node (p> 0,05). Comparing the tests used in Kaplan-Meier method, there was a significant difference in survival time compared to Log Rank (Mantel-Cox) test only (p <0,05). In Cox regression method, there is a significant difference in survival time compared to lymph node (p <0,05). There was a significant difference in terms of survival according to recurrence status, location of recurrence and type of metastasis (p <0,05). According to the comparison of the tests used in Kaplan-Meier method, there was a significant difference in terms of survival according to recurrence status, recurrence site and metastasis type (p <0,05). In Cox regression method, there was a significant difference in terms of survival time according to recurrence status, site of recurrence and type of metastasis (p <0,05). Conclusion: In our study, the applicability of survival analysis method on breast cancer patients was demonstrated. It yielded similar results in all three methods of survival analysis. Key words: Survival analysis, Life table analysis, Kaplan-Meier analysis, Cox Regression analysis