Bladder cancer is one of the most common malignancies of the urinary system and is characterized by high recurrence rates and poor long-term outcomes. Early detection and accurate diagnosis are essential for improving clinical management.
This prospective diagnostic accuracy study aims to develop and validate a precision diagnostic model for bladder cancer based on microfluidic isolation and multiplex detection of urinary exosomes.
A novel microfluidic platform will be developed for rapid and efficient urinary exosome enrichment. Multi-omics approaches, including RNA sequencing and proteomic profiling, will be used to identify bladder cancer-associated urinary exosome biomarkers. A multiplex microfluidic detection chip will subsequently be developed for simultaneous detection of multiple biomarkers.
A diagnostic model integrating urinary exosome biomarker profiles and clinical characteristics will be developed in a training cohort and prospectively validated in an independent cohort. Diagnostic performance will be evaluated using pathological diagnosis as the reference standard.
This study aims to establish a non-invasive, rapid, and accurate diagnostic strategy for bladder cancer.
Inclusion Criteria:
1. Age ≥18 years.
2. Patients with bladder cancer confirmed by pathological examination.
3. Patients with benign urological diseases confirmed by clinical evaluation.
4. Ability to provide urine samples and relevant clinical information.
5. Written informed consent provided.
Exclusion Criteria:
1. History of other malignant tumors, except participants specifically included in the validation cohort.
2. Severe organ dysfunction.
3. Glomerulonephritis.
4. Recent significant urinary tract injury.
5. Inadequate urine sample availability.
Participants with pathologically confirmed bladder cancer, including non-muscle-invasive bladder cancer (Ta and T1) and muscle-invasive bladder cancer (≥T2).
Participants diagnosed with benign urological diseases without evidence of malignancy.
Participants with other urinary system malignancies included for evaluation of diagnostic specificity during the validation phase.
Beijing, Beijing Municipality 100021, China
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