Background: Bladder cancer is a prevalent malignancy of the urinary system, exhibiting extraordinarily complex pathogenesis involving multidimensional interactions between genetic and environmental factors. Substantial evidence confirms the pivotal role of genetic determinants in bladder carcinogenesis and progression. Although genome-wide association studies (GWAS) have successfully identified multiple genetic variants potentially associated with bladder cancer, the population-specific genetic architecture and its clinical implications in the Han Chinese patients remain to be elucidated.

Methods: This study developed a detection system for single nucleotide polymorphisms (SNPs) using multiplex polymerase chain reaction (PCR), single-base extension (SBE), and capillary electrophoresis technology, aimed at identifying potentially pathogenic variants. The method was applied to analyze 142 samples obtained from the Han Chinese individuals (aged 15–82, with an average age of 58 years) into a case group (n = 71) and a control group (n = 71).

Results: Statistical analysis revealed five SNPs with significant association in the case group. Binary Logistic regression analysis further validated its application for disease risk assessment and prediction. A predictive model integrating four significant SNPs, including rs8102137, rs7747724, rs1258767, and rs2042329, yielded an area under the curve (AUC) of 0.797 for predicting bladder cancer, while multifactor dimensionality reduction (MDR) analysis achieved a balanced accuracy of 0.7543.

Conclusion: This study demonstrates that these SNPs hold significant potential for application in genetic testing to predict bladder cancer risk; however, further research is needed to elucidate their functional mechanisms. Our analysis provides comprehensive insights into the association between bladder cancer-related genetic polymorphisms, hereditary susceptibility, and disease progression. These results establish a theoretical foundation for improving early diagnosis, preventive measures, and personalized treatment strategies in bladder cancer.