Glycan alterations, or glycovariants (GV), are well-recognized features of malignant transformation and are commonly observed in several cancers, including bladder cancer (BlCa). However, their integration into practical diagnostic assays remains limited. Here, we investigated whether glycan modifications on the urinary glycoproteins mucin 1 (MUC1) and carcinoembryonic antigen (CEA) could serve as diagnostic indicators for BlCa diagnosis. MUC1 and CEA were captured directly from urine samples of patients with benign prostate disease (n = 20) and BlCa (n = 19) by immobilizing monoclonal antibodies against these glycoproteins on microtitration wells. Cancer-associated glycan structures were detected using wheat germ agglutinin (WGA) lectin and glycan-specific antibody C241 (a clone of anti-carbohydrate antigen 19–9), both conjugated to Eu⁺³-doped nanoparticles. This glycovariant-based detection approach enables selective recognition of disease-associated glycoforms. By combining assay results, several models were constructed to evaluate marker panels with improved sensitivity and selectivity. A combined diagnostic model incorporating MUC1-WGA and CEA-C241 immunoassays, designed to detect N-acetylglucosamine (GlcNAc) on MUC1 and sialyl-Lewis^a (sLe^a) structures on CEA, achieved approximately 95% sensitivity and 95% selectivity for identifying bladder cancer. The MUC1-WGA assay alone distinguished cases with 79% sensitivity and 95% selectivity, while other individual GV assays demonstrated comparatively lower sensitivities. In contrast, conventional protein-level measurements showed lower diagnostic performance. Concurrent detection of glycan alterations on MUC1 and CEA improved discrimination between bladder cancer and benign conditions. This GV-assay framework provides a modular platform that can be extended to incorporate additional urinary biomarkers. However, validation in larger patient cohorts is required to confirm clinical applicability.