Prognostic Significance of Lymphovascular Invasion in Breast Cancer: Insights From a Retrospective Analysis at a Tertiary Care Center.

OBJECTIVE

To explore the relationship between lymphovascular invasion (LVI) and outcomes across different histopathological subtypes, tumor grades, clinical stages, hormone receptor profiles, and treatment modalities. Lymphovascular invasion is a well-recognized histopathological feature associated with tumor dissemination in breast cancer. However, its prognostic weight is under-reported in Middle Eastern cohorts.

METHODS

We retrospectively reviewed data from 828 women treated for invasive breast carcinoma at King Abdulaziz University Hospital from 2010 to 2020. Clinicopathologic variables, treatments, and outcomes were extracted. Overall survival (OS) and event-free survival (EFS) were estimated and tested using Kaplan-Meier curves; independent predictors were identified with stepwise Cox models.

RESULTS

Lymphovascular invasion was identified in 31.5% of cases, and Kaplan-Meier analysis revealed significantly reduced mean OS (9.94 vs. 12.43 years; p < 0.001) and EFS (8.33 vs. 11.23 years; p < 0.001) in these patients. Multivariable analysis adjusted for established clinicopathological covariates indicated LVI as an independent predictor of poorer EFS (HR = 1.909, 95% CI 1.218-2.992; p = 0.005). Additionally, positive estrogen receptor status conferred lower risk (HR = 0.543; 95% CI: 0.345-0.853; p = 0.008), while higher pathological N stages (N2 and N3) were correlated with significantly increased hazard ratios for recurrence or death (HR = 3.515 and 4.479, respectively; both p < 0.01). Notably, the adverse prognostic impact of LVI persisted across different histological subtypes, hormonal profiles, and treatment modalities.

CONCLUSION

Our findings underscore LVI as a robust and independent prognostic factor for poor survival outcomes in breast cancer, with implications for multiple clinicopathologic and therapeutic contexts. These results support the routine incorporation of LVI into prognostic models and treatment algorithms in breast cancer management.