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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
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《Journal of Clinical Medicine》
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The diagnostic effectiveness of serum sialic acid predicts both qualitative and quantitative prostate cancer in patients with prostate-specific antigen between 4 and 20 ng/mL.
This study aimed to evaluate the predictive value of the serum biochemical index, including alkaline phosphatase (AKP), lactate dehydrogenase (LDH), α-L-fucosidase (AFU), serum sialic acid (SA), and fibrinogen (FIB), for prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) in patients with a prostate-specific antigen (PSA) value between 4 and 20 ng/mL.
This study retrospectively examined the clinical data of 408 eligible patients who underwent prostate biopsies in our hospital between March 2015 and July 2022. CSPCa was defined as a "Gleason grade group of≥2". For analyzing the association between PCa/CSPCa and serum biochemical index, univariable logistic regression and multivariable logistic regression were conducted. Based on the multivariable logistic regression model, we constructed models and compared the area under the curve (AUC). We generated the nomogram, the ROC curve, the DCA curve, and the calibration curve for PCa.
Overall, we studied 271 patients with PCa (including 155 patients with CSPCa) and 137 non-PCa patients. Patients with PCa were more likely to consume alcohol, have higher total PSA (TPSA) values, and have lower free PSA (FPSA) and free/total PSA (f/T) values. There were higher TPSA values and lower f/T values in the CSPCa group when compared with the non-CSPCa group. The univariate logistic regression analyses did not show significant results. However, AKP, AFU, SA, TPSA, and FPSA all retain significant significance when all factors are included in multifactor logistic regression analysis. This finding suggests that the exposure factor exhibited an independent effect on the outcome after controlling for other factors, including the potential confounding effects that may have been underestimated. Through ROC curves, we found that SA and TPSA levels are more powerful predictors. In contrast, there is a lack of excellent predictive value for PCA and CSPCa using Age, AFU, FIB, and FPSA.
In our study, serum biochemical index is a potential prediction tool for PCa and CSPCa for patients with PSA values between 4 and 20 ng/mL. Additionally, the new serum biochemical index SA is also useful when diagnosing PCa and CSPCa, as we conclude in our study.
Sun J
,Yan L
《Frontiers in Endocrinology》
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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
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《Frontiers in Oncology》
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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
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《Frontiers in Oncology》
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Predictive value of the monocyte-to-lymphocyte ratio in the diagnosis of prostate cancer.
It has been reported that inflammation and immune system are related to prostate cancer. The neutrophil-to-lymphocyte ratio (NLR), as well as the platelet-to-lymphocyte ratio (PLR), have already been proposed as new indices to help diagnose prostate cancer (PCa). However, the monocyte-to-lymphocyte ratio (MLR) with regard to PCa has rarely been mentioned.To investigate the capability of the MLR to predict PCa.Patients who were pathologically diagnosed with PCa in our hospital and healthy control subjects who conformed to the inclusion criteria were enrolled. Patient data were recorded, including age, complete blood counts, blood biochemistry, and serum prostate-specific antigen (PSA) levels. The differences in these data between the groups were analyzed and the diagnostic value of the MLR was compared with PSA.Our study included a total of 100 patients with PCa and 103 healthy control subjects. Patients with PCa presented with a significantly higher NLR, MLR, and PLR compared to control subjects. However, the hemoglobin and lymphocyte levels were lower (P < .05) in PCa patients. The area under the curve (AUC) of PSA and ratio of free/total serum prostate-specific antigen were 0.899 (95% confidence interval [CI]: 0.857-0.942) and 0.872 (95% CI: 0.818-0.926), respectively, while the AUC of the MLR was 0.852 (95% CI: 0.798-0.906), which was higher than that of the NLR, PLR, and any other blood parameters. Additionally, the optimal cut-off value of the MLR for PCa was 0.264, with a specificity of 87.4% and a sensitivity of 72.0%. An evaluation of the diagnostic value of MLR + PSA gave an AUC of 0.936 (95% CI: 0.902-0.970). However, the AUC of MLR + PSA + f/tPSA was 0.996 (95% CI: 0.991-1.000). The diagnostic value of MLR + NLR + PSA gave an AUC of 0.945 (95% CI: 0.913-0.977), and the specificity is 0.971.PSA remains the most important diagnostic indicator. MLR combined with PSA and f/tPSA has the higher predictive value than PSA. It suggests that MLR may be another good predictive indicator of PCa. It can help reduce the clinical false positive rate.
Xu Z
,Zhang J
,Zhong Y
,Mai Y
,Huang D
,Wei W
,Huang J
,Zhao P
,Lin F
,Jin J
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