Bladder transitional cell carcinoma anatomic primary site as a predictor of survival and mortality: a population-based retrospective cohort study.

BACKGROUND

Bladder cancer is a heterogeneous disease with varying prognostic outcomes based on the primary tumor site within the bladder. This study aims to evaluate the impact of tumor location on overall survival and cancer-specific survival in bladder cancer patients.

METHODS

The authors conducted a retrospective cohort study using data from the Surveillance, Epidemiology, and End Results database. Patients with primary transitional cell carcinoma of the bladder were categorized based on their tumor locations. Survival outcomes were assessed using Kaplan-Meier analysis and Cox proportional hazards regression models, adjusted for age, sex, race, cancer stage, and treatment modalities. Additionally, binary logistic regression models were employed to predict overall mortality (OM) and cancer-specific mortality (CSM) at 1, 5, and 10 years.

RESULTS

The study included 107 909 patients diagnosed with primary bladder cancer between 2000 and 2021. Significant differences in survival outcomes were observed across different tumor sites. Bladder cancer originating in the urachus had the worst OS before 100 months and the worst CSS overall. Tumors in the anterior wall showed the worst OS after 100 months. In the Cox multivariable analysis, anterior wall tumors were associated with a 1.513-fold increased risk of death compared to lateral wall tumors. The binary logistic regression models showed that anterior wall tumors predicted the highest OM and CSM at 1-year, while urachal tumors had the worst outcomes at 5 and 10 years.

CONCLUSIONS

The primary site of bladder cancer is a significant predictor of survival outcomes, with tumors in the urachus and anterior wall associated with a poorer prognosis. These findings underscore the importance of considering tumor location in the prognosis and management of bladder cancer. Future studies should aim to validate these findings in more diverse populations and explore the underlying biological mechanisms that drive these differences.