
Survival Analysis: A Hospital Based Retrospective Life Span Study of Breast Cancer Patients after First Recurrence
Author(s) -
Madiha Liaqat,
Waqas Fazil
Publication year - 2020
Language(s) - English
DOI - 10.47363/jcrr/2020(2)105
Subject(s) - breast cancer , medicine , proportional hazards model , hazard ratio , oncology , cancer , radiation therapy , confidence interval , gynecology , disease
Background Overall survival of breast cancer patients has been calculated many times but there is no precise research available regarding the survival time of breast cancer patients after recurrence. We investigated the effects factors on mortality due to breast cancer. Methods All Factors were analyzed using statistical tools and techniques to find out rate of mortality after recurrence. Descriptive statistics, cox proportional hazard models were used to find statistical significant variables. In the present study recurrence is considered as an important event which may play a role in study of breast cancer progression. In this study, we evaluated breast cancer risk factors in relation to mortality due to this disease among 1028 women with breast cancer in Lahore, Pakistan. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between risk factors and mortality due to breast cancer were estimated in subtype-specific Cox regression models. Results Survival of breast cancer patients depends upon many factors. A total of 581 alive and 447 deaths due to breast cancer occurred during a median follow-up period of 1977 days. Median survival time after recurrence was 3 years. Significant factors were included post- menopausal women who diagnosed and had recurrence at the age 5. Radiotherapy has increased life span of patients even after recurrence. Conclusion Younger women had higher risk of mortality after recurrence even gone through chemotherapy while lower grade tumor had good prognosis. Radiotherapy played a major role in increasing life time of breast cancer women after recurrence. Our findings are consistent with those from previously published data.