LAUSR

INTRODUCTION Previous studies have revealed that Gleason score upgrading (GSU) was closely related to an increased biochemical recurrence rate and adverse oncologic outcomes in patients with prostate cancer (PC). Therefore, we performed a meta-analysis to determine the predictive factors for GSU following radical prostatectomy (RP). METHODS We performed an extensive literature search using PubMed, Embase, and Cochrane in September 2022. In order to calculate the pooled odds ratio (OR), standardized mean difference (SMD), and 95% confidence intervals, a fixed effect or a DerSimonian and Laird random effect was applied. RESULTS Twenty-six studies included 18,745 PC patients that were available for further analysis. Our results revealed that GSU was significantly correlated with age (summary SMD = 0.13; p = 0.004), prostate volume (PV) (summary SMD = -0.19;p < 0.001), preoperative PSA (p-PSA) (summary SMD = 0.18; p < 0.001), PSA density (PSAD) (summary SMD = 0.40; p < 0.001), number of positive cores (summary SMD = 0.28; p = 0.001), percentage of positive cores (summary SMD = 0.36; p < 0.001), Prostate Imaging Reporting and Data System (PI-RADS) scores (>3/≤3) (summary OR = 2.27; p = 0.001), clinical T stage (>T2/≤T2) (summary OR = 1.73; p < 0.001), positive surgical margins (PSM) (summary OR = 2.12; p < 0.001), extraprostatic extension (EPE) (summary OR = 2.73; p < 0.001), pathological T stage (>T2/≤T2) (summary OR = 3.45; p < 0.001), perineural invasion (PNI) (summary OR = 2.40; p = 0.008), and neutrophil to lymphocyte ratio (NLR) (summary SMD = 0.50; p < 0.001). However, we found that GSU was not significantly correlated with body mass index (BMI) (summary SMD = -0.02; p = 0.602). Moreover, our sensitivity and subgroup analyses showed that the findings were reliable. CONCLUSIONS Age, PV, p-PSA, PSAD, number of positive cores, percentage of positive cores, PI-RADS score, clinical T stage, PSM, EPE, pathological T stage, PNI, and NLR are independent factors predicting GSU following RP. The findings may be helpful in risk stratification and personalized treatment in PC patients.