The serum prostate-specific antigen (PSA) testing is widely used for prostate cancer (PCa) screening but suffers from poor specificity, leading to unnecessary biopsies and overtreatment. The significant potential of extracellular vesicles (EVs) in cancer diagnosis has driven the development of efficient methods to isolate and identify EV biomarkers from large-scale clinical samples. Here, we systematically evaluate five commonly used EV isolation techniques through proteomic profiling of plasma-derived EVs, endorsing TiO2-based chemical affinity capture as a superior approach for analyzing EVs from complex clinical samples. This method demonstrates exceptional advantages in speed, throughput, reproducibility, and protein coverage. Using this optimized workflow, we analyzed plasma EVs from 80 patients with PCa and benign prostatic hyperplasia (BPH), identifying growth differentiation factor 15 (GDF15) as a compelling biomarker with a predictive power (AUC) of 0.908 for PCa. Extensive validation across independent cohorts comprising 457 samples, including plasma EVs and prostate tissues, confirmed GDF15's ability to distinguish PCa from BPH and stratify PCa stages. Notably, the combination of GDF15 with PSA further enhanced diagnostic efficiency, particularly for patients in the PSA diagnostic gray zone. This study establishes a robust workflow for EV protein analysis in large clinical cohorts and highlights EV-GDF15 as a promising biomarker for noninvasive PCa diagnosis.