Objective: Grading discordance between transrectal ultrasound (TRUS)-guided biopsy and radical prostatectomy (RP) specimens represents a clinically significant challenge in prostate cancer management. This study aimed to evaluate the concordance of Gleason score (GS) and prognostic grade group (GG) between TRUS-guided biopsy and RP specimens, and to identify histopathological parameters associated with grading discordance.
Materials and
Methods: This retrospective study included 88 patients who underwent TRUS-guided biopsy followed by RP between 2023 and 2026. All biopsy and RP specimens were re-evaluated by two pathologists according to 2019 ISUP consensus criteria. Grading changes were classified as concordant, upgraded, or downgraded. Cohen’s kappa coefficient and Spearman correlation were used to assess agreement and correlation. Clinicopathological parameters associated with GG change were analyzed using Chi-square and Fisher’s exact tests.

Results: The mean patient age was 66.41±6.5 years. GS and GG concordance was 64.8% (n=57), upgrading was observed in 29.5% (n=26), and downgrading in 5.7% (n=5). Moderate agreement was found for both GS (κ=0.458) and GG (κ=0.456), with significant positive correlations (Spearman rho=0.680 and 0.703, respectively; p<0.001). Biopsy tumor volume (p=0.005), perineural invasion (p=0.044), and pattern 4 ratio (p=0.028) were significantly associated with GG change. Among RP parameters, extraprostatic extension (p=0.002), perineural invasion (p=0.006), surgical margin status (p=0.021), and tumor volume (p=0.018) were significantly related to grading discordance. Age and pre-biopsy PSA level showed no significant association with GG change.

Conclusion: TRUS-guided biopsy demonstrated moderate concordance with RP specimens. Biopsy-derived parameters including tumor volume, perineural invasion, and pattern 4 ratios provide valuable predictive information for grading discordance. These findings highlight the importance of systematically integrating routine histopathological data into clinical decision-making to optimize patient management.