The Values of Systemic Immune-Inflammation Index and Neutrophil-Lymphocyte Ratio in the Localized Prostate Cancer and Benign Prostate Hyperplasia: A Retrospective Clinical Study.

To evaluate the diagnostic values of systemic immune-inflammation index (SII) and neutrophil-lymphocyte ratio (NLR) in patients with localized prostate cancer (PCa). Between January 2014 and December 2019, 117 patients with benign prostate hyperplasia (BPH) and 278 patients with localized PCa who underwent radical prostatectomy (RP) were included in this study. The inflammatory markers including SII, NLR, platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), lymphocyte ratio (LR), neutrophil ratio (NR), mean platelet volume (MPV), and red cell distribution (RDW) of these two groups were examined and analyzed. ROC curve analysis was performed to assess the discriminative ability of inflammatory markers and their combination with tPSA for PCa. The binary logistic regression model was used to evaluate the association between significant inflammatory markers and risk of PCa. The pathological results from RP specimen comprised 72 (25.90%) patients with pT1, 168 (60.43%) patients with pT2, and 38 (13.67%) patients with pT3. According to Student's t test, patients with PCa had higher NLR (p = 0.034), SII (p = 0.008), and NR (p = 0.004), and lower LR (p = 0.025), MPV (p = 0.003), and TPV (p = 0.022) compared with patients with BPH; the distribution of age, PLR, LMR, RDW, f/t PSA ratio, and BMI did not show any significant differences. The AUC for NLR, SII, NR, and tPSA was 0.697 (p = 0.015), 0.719 (p < 0.001), 0.647 (p = 0.009), and 0.708 (p < 0.001), with threshold values of 1.6, 471.86, 65.15%, and 12.89 ng/ml, respectively. Patients were divided into two groups according to the threshold values, respectively. By using the multivariable logistic regression models, NLR ≥ 1.6 (OR, 2.731; 95% CI, 0.937-7.961, p = 0.042), SII ≥ 471.86 (OR, 1.274; 95% CI 0.473-3.433; p = 0.033), and PSA ≥ 12.89 ng/ml (OR, 1.443; 95% CI, 0.628-3.944; p = 0.014) were independent risk factors associated with PCa. The AUC for combination of NLR, SII, and NR with tPSA was 0.705 (p < 0.001), 0.725 (p < 0.001), and 0.704 (p < 0.001), respectively. This study demonstrated that SII, NLR, and NR were all independent risk factors of PCa. These factors alone could provide better screen methods for PCa before biopsy. In addition, SII is a more powerful tool among these three inflammatory markers associated with PCa. Besides, combination of SII and NLR with tPSA had not much advantage compared with themselves alone.

Wang S ，Ji Y ，Chen Y ，Du P ，Cao Y ，Yang X ，Ma J ，Yu Z ，Yang Y ... -  《Frontiers in Oncology》

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

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). The data of 297 patients who underwent prostate biopsy and RP in our center from January 2014 to March 2020 were retrospectively analyzed. Preoperative clinical characteristics including age, values of tPSA, total prostate volume (TPV), f/t PSA ratio, body mass index (BMI), biopsy GS and inflammatory factors including SII, NLR, lymphocyte to monocyte (LMR), neutrophil ratio (NR), platelet to lymphocyte ratio (PLR), lymphocyte ratio (LR), mean platelet volume (MPV) and red cell distribution (RDW) 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 used to confirm the discriminative ability of inflammatory factors including SII, NLR and their combination with tPSA for predicting GS and GSU. By using univariate and multivariate logistic regression analysis, the association between significant inflammatory markers and grades of GS were evaluated. Patients enrolled were divided into low (GS ≤ 6) and high (GS≥7) groups by the grades of GS. The median values of clinical factors were 66.08 ± 6.04 years for age, 36.62 ± 23.15 mL for TPV, 26.16 ± 33.59 ng/mL for tPSA and 0.15 ± 0.25 for f/t PSA ratio, 22.34 ± 3.14 kg/m2 for BMI, 15 (5.1%) were pT1, 116 (39.1%) were pT2 and 166 (55.9%) were pT3. According to the student's t test, patients in high GS group had a greater proportion of patients with pT3 (P<0.001), and higher NLR (P=0.04), SII (P=0.037) and tPSA (P=0.015) compared with low GS group, the distribution of age, TPV, f/t PSA ratio, BMI, LMR, NR, PLR, LR, MPV and RDW did not show any significantly statistical differences. The AUC for SII, NLR and tPSA was 0.732 (P=0.007), 0.649 (P=0.045) and 0.711 (P=0.015), with threshold values of 51l.08, 2.3 and 10.31ng/mL, respectively. According to the multivariable logistic regression models, NLR ≥ 2.3 (OR, 2.463; 95% CI, 0.679-10.469, P=0.042), SII ≥ 511.08 (OR, 3.519; 95% CI 0.891-12.488; P=0.003) and tPSA ≥ 10.31 ng/mL (OR, 4.146; 95% CI, 1.12-15.35; P=0.033) were all independent risk factors associated with higher GS. The AUC for combination of SII, NLR with tPSA was 0.758 (P=0.003) and 0.756 (P=0.003), 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, P=0.001, 0.044, 0.017, <0.001 and <0.001, respectively. High SII, NLR and tPSA were associated with higher GS and higher GSU rate. SII was likely to be a more favorable biomarker for it had the largest AUC area compared with tPSA and NLR; the combination of SII or NLR with tPSA had greater values for predicting GS and GSU compared with NLR, SII or tPSA alone, since the AUC area of combination was much higher. SII, NLR were all useful inflammatory biomarkers for predicting GS and detecting GSU among localized PCa patients with biopsy GS ≤ 6.

Wang S ，Ji Y ，Ma J ，Du P ，Cao Y ，Yang X ，Yu Z ，Yang Y ... -  《Frontiers in Oncology》

The values of systemic immune-inflammation index and neutrophil-lymphocyte ratio in predicting testicular germ cell tumors: A retrospective clinical study.

To determine whether complete blood count (CBC) based inflammatory parameters can be used as markers predicting testicular germ cell tumors (TGCT). Between 2013 to 2018 the data of 58 patients with testicular TGCT undergoing radical orchiectomy and 54 malignancy-free healthy men were retrospectively analyzed as tumor group and control group. Patient baseline characteristics including age, pathological stage and pre-surgery CBC based inflammatory parameters including neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), systemic immune-inflammation index (SII), lymphocyte ratio (LR), neutrophil ratio (NR), mean platelet volume (MPV) and red cell distribution width (RDW) were analyzed and compared between tumor group and control group. Receiver operating characteristic (ROC) curve were used analyzing data with significantly difference to assess the discriminative ability of the markers for TGCT, area under the curve (AUC), cut-off value, sensitivity and specificity were calculated. The binary logistic regression model was used to evaluate the association between significant inflammatory markers and risk of TGCT. Mean age of the tumor and control group was 41.1 ± 15.36 and 44.89 ± 9.2 years, respectively. Mean NLR, SII and RDW were significantly higher in tumor group compared with control group with P=0.005, P=0.001 and P=0.016, respectively; there were no significantly differences of age, PLR, LMR, LR, NR, MPV and RDW between groups. The ROC curve for NLR, SII and RDW was plotted in the diagnosis of TGCT and tumor progression, the cut-off value for NLR, SII and RDW were found as 3.38 (AUC: 0.704, sensitivity=51.4%, specificity=88.6%, P=0.003), 881.24 (AUC: 0.725, sensitivity=45.7%, specificity=91.4%, P=0.001) and 0.14 (AUC: 0.63, sensitivity=28.6%, specificity=97%, P=0.063), respectively. Patients were divided into two groups according to the threshold values, respectively. By using the multivariable logistic regression models, NLR ≥ 3.38 (OR, 5.86; 95% CI, 1.67-20.65, P=0.006) and SII ≥ 881.24 (OR, 4.89; 95% CI, 1.48-15.32, P=0.009) were independent risk factors predicting TGCT. Significantly statistical difference of pathological stage was also found between groups with respect to NLR cut-off values (P=0.034) and SII cut-off values (P=0.049). Combined the data together, NLR and SII both exhibited good differential diagnosis potential which could be used as markers predicting the TGCT. As the CBC based inflammation parameters, both NLR and SII could be used as effective tumor markers predicting the TGCT, and higher NLR and SII are associated with higher pathological stage. In addition, SII is a more powerful tool among these two inflammatory markers.

Wang S ，Yang X ，Yu Z ，Du P ，Cao Y ，Ji Y ，Ma J ，Yang Y ... -  《Frontiers in Oncology》

The Values of Systemic Immune-Inflammation Index and Neutrophil-Lymphocyte Ratio in Predicting Biochemical Recurrence in Patients With Localized Prostate Cancer After Radical Prostatectomy.

To investigate the association between preoperative systemic immune-inflammation index (SII) and neutrophil-lymphocyte ratio (NLR) and oncological outcomes in localized prostate cancer (PCa) patients after radical prostatectomy (RP). Between January 2014 and December 2019, 291 patients with pathologically confirmed localized PCa who underwent RP were included in this study. The threshold values of SII and NLR for biochemical recurrence (BCR) were calculated according to Youden's index based on the receiver operating characteristic (ROC) curve, then the patients were divided into two groups by the threshold values of SII and NLR, and the clinicopathological outcomes were analyzed and compared between groups, respectively. The binary logistic regression model was used to evaluate the association between SII, NLR, and pathological outcomes including Gleason score (GS) and pathological T (pT) stage. Kaplan-Meier curves and univariable and multivariable Cox regression models were used to determine the association between high SII, high NLR, and BCR-free survival, respectively. The median follow-up time was 48 months (IQR 36-62), and 114 (39.18%) patients developed BCR. The AUC of SII for BCR was 0.813 (P < 0.001), with a threshold value of 528.54, a sensitivity of 72.9%, and a specificity of 76.3%; the AUC of NLR for BCR was 0.824 (P < 0.001), with a threshold value of 2.62, a sensitivity of 71.2%, and a specificity of 81.6%. Patients were divided into two groups according to the threshold values of SII and NLR, respectively. Patients in the high SII group had higher tPSA, GS, pT stage, and BCR rate than patients in the low SII group (P = 0.004, 0.04, 0.007, and <0.001, respectively), and patients in the high NLR group had higher tPSA, GS, pT stage, and BCR rate than patients in the low NLR group (P = 0.04, 0.02, 0.006, and <0.001, respectively). Multivariable logistic regression analysis revealed that high SII was significantly correlated with adverse pathological outcomes of GS (HR, 1.656; 95% CI, 1.00-2.742, P = 0.042) and pT stage (HR, 1.478; 95% CI, 0.972-3.64, P = 0.028); there was no association between high NLR and pathological events. Kaplan-Meier analysis showed significantly poorer BCR-free survival in patients with high SII or high NLR (P < 0.001 and <0.001, respectively). By using the multivariable Cox regression model, high SII (HR, 4.521; 95% CI, 2.262-9.037, P < 0.001) and high NLR (HR, 4.787; 95% CI, 2.339-9.798, P < 0.001) were both significant predictors of BCR after RP. High SII was significantly related to unfavorable clinicopathological outcomes. High preoperative SII and NLR were related to higher BCR rate in localized PCa after RP, and they were all independent risk factors associated with shorter BCR-free survival. These two factors might provide promising and inexpensive methods for predicting clinical outcomes in patients with RP.

Wang S ，Yang X ，Yu Z ，Du P ，Sheng X ，Cao Y ，Yan X ，Ma J ，Yang Y ... -  《Frontiers in Oncology》

Diagnostic Efficiency of Pan-Immune-Inflammation Value to Predict Prostate Cancer in Patients with Prostate-Specific Antigen between 4 and 20 ng/mL.

Zhu M ，Zhou Y ，Liu Z ，Jiang Z ，Qi W ，Chen S ，Wang W ，Shi B ，Zhu Y ... -  《Journal of Clinical Medicine》