AUTHOR=Wang Shuo , Ji Yongpeng , Ma Jinchao , Du Peng , Cao Yudong , Yang Xiao , Yu Ziyi , Yang Yong 

TITLE=Role of inflammatory factors in prediction of Gleason score and its upgrading in localized prostate cancer patients after radical prostatectomy

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1079622

DOI=10.3389/fonc.2022.1079622

ISSN=2234-943X

ABSTRACT=Purpose To investigate the role of inflammatory factors including systemic immune-inflammation index (SII) and neutrophil to lymphocyte ratio (NLR) in predicting Gleason Score (GS) and Gleason Score upgrading (GSU) in localized prostate cancer (PCa) after radical prostatectomy (RP). 
Methods The data of 297 patients who underwent prostate biopsy and RP in our center were retrospectively analyzed. Preoperative clinical characteristics and inflammatory factors including SII, NLR as well as pathological T (pT) stage were collected and compared according to the grades of RP GS (GS≤6 and GS≥7), respectively. ROC curve analysis was performed to assess the discriminative ability of inflammatory factors including SII, NLR and their combination with tPSA for predicting GS and GSU. Univariate analysis and multivariate logistic regression analysis were used to evaluate the association between significant inflammatory markers and grades of GS.
Results Patients enrolled were divided into low (GS≤6) and high (GS≥7) groups by the grades of GS. According to the student’s t test, patients in high GS group had a greater proportion of pT3 stage, and higher NLR, SII and tPSA compared with low GS group. The AUC for SII, NLR and tPSA was 0.732, 0.649 and 0.711, with threshold values of 51l.08, 2.3 and 10.31ng/mL, respectively. By using the multivariable logistic regression models, NLR, SII and tPSA were all independent risk factors associated with higher GS. The AUC for combination of SII, NLR with tPSA was 0.758 and 0.756, respectively. GSU was observed in a total of 48 patients with GS ≤ 6 (55.17%). Then patients were divided into 2 groups (high and low) according to the threshold value of SII, NLR, tPSA, SII+tPSA and NLR+tPSA, respectively, when the GSU rates were compared with regard to these factors, GSU rate in high level group was significantly higher than that in low level group.
Conclusion High SII, NLR and tPSA were associated with higher GS and higher GSU rate. SII seemed be a more favorable biomarker for it had the largest AUC area; the combination of SII or NLR with tPSA had great value for predicting GS and GSU compared with SII, NLR or tPSA alone.