Affiliation:
1. Department of Medical Oncology, Regional Cancer Centre, Thiruvananthapuram, Kerala, India
2. Department of Radiation Oncology, Regional Cancer Centre, Thiruvananthapuram, Kerala
Abstract
Objectives The lack of data on management of elderly breast cancer patients' population makes most oncologists reluctant to treat them with the standard treatment protocols as advised for the younger patients. This study was done to identify the survival outcome and predictors of survival in elderly breast cancer patients treated with curative intent.
Materials and Methods Newly diagnosed patients with breast cancer aged more than 65 years who received treatment with curative intent were included. Disease-free survival (DFS) and overall survival were estimated using the Kaplan–Meier method. Survival curves were compared using log-rank test. Cox regression analysis was done to find out the predictors of DFS.
Results This study included 112 elderly breast cancer patients. In our patient population, 79 (70.5%) were less than or equal to 70 years of age and 33 (29.5%) were more than or equal to 70 years. Median age was 68 years. Charlson comorbidity index score was six and above in 31 (28.1) patients. Median DFS in our study was 46 months. Median DFS was not reached in patients less than or equal to 70 years of age, whereas it was 50 months (47–53) among patients more than or equal to 70 years of age, p-value-0.009. In univariate analysis, age more than or equal to 70 years and locally advanced breast cancer were the predictors of DFS with hazard ratio (HR) of 2.8 (1.2–6.69), p-value 0.013 and 2.9 (1.12–7.6), and 0.027, respectively. In multivariate analysis, age more than or equal to 70 years was the only significant predictors of DFS with HR of 2.8 (1.2–6.5) and p-value of 0.015.
Conclusion Standard curative intent treatment was well tolerable among elderly patents. Elderly age more than 70 years was a unique predictor of DFS. We need to incorporate tools to assess life expectancy and functional status that will help us predict toxicity of treatment and survival advantage more precisely.