Disease Free Survival in Locally Advanced Breast Cancer: An Analysis of Clinical and Pathological Factors - Anuj Sharma Singh; Barasha Sarma Bhardwaj; B.C Goswami (Asian Pacific Journal of Cancer Care, 2022)
Background: The TNM stage is the widely accepted tool to predict prognosis in breast cancer cases, but it deals with a limited range of factors and ignores patient-specific conditions, pathological or genotype characteristics and treatments. The purpose of this study was to evaluate if and how different clinical (tobacco chewing, age etc) and pathological (lymphovascular and perineural invasion etc) variables influence the disease free survival. Material and Methods: This study involves North Eastern Indian population. Data of 101 patients with locally advanced breast cancer diagnosed in the time period of January to December 2018 was probed and they were followed up till March 2020. Association between various clinicopathological risk factors and disease free survival was assessed using univariate and multivariate models. Survival estimates were computed using the Kaplan-Meier method and differences between survival times were assessed by means of the Log rank test. Multivariate analyses were carried out using Cox’s proportional hazards model. Results: During follow up period 14 patients developed metastasis. There was significantly reduced disease free survival seen trough Kaplan Meier plots in patients having tumor size >6 cm, N2/ N3 stage, triple negative receptor status, tobacco chewing and positive perineural invasion. Multivariate analysis revealed that stage (N2, N3) and positive perineural invasion are two independent variables which adversely affect the survival. Conclusion: Bottom line of the study is that, disease free survival in LABC patients is significantly reduced with higher stage (N2, N3) and positive perineural invasion as revealed by multivariate analysis. Three other factors which adversely affect DFS are tobacco chewing, tumor size > 6cm and triple negative hormone receptor status according to univariate analysis.