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全免疫炎症值对前列腺特异性抗原在4至20 ng/mL之间的患者预测前列腺癌的诊断效能

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

作者信息

Zhu Meikai, Zhou Yongheng, Liu Zhifeng, Jiang Zhiwen, Qi Wenqiang, Chen Shouzhen, Wang Wenfu, Shi Benkang, Zhu Yaofeng

机构信息

Department of Urology, Qilu Hospital of Shandong University, Jinan 250012, China.

Department of Urology, Tai'an City Central Hospital, Tai'an 271000, China.

出版信息

J Clin Med. 2023 Jan 19;12(3):820. doi: 10.3390/jcm12030820.

Abstract

INTRODUCTION

To evaluate the predictive value of the pan-immune-inflammation value (PIV) and other systemic inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), 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.

PATIENTS AND METHODS

The clinical data of 319 eligible patients who underwent prostate biopsies in our hospital from August 2019 to June 2022 were retrospectively analyzed. CSPCa was defined as a "Gleason grade group of ≥2". A univariable logistic regression analysis and multivariable logistic regression analysis were conducted to analyze the association between the PIV, SII, MLR, and PCa/CSPCa. For the inflammatory indicators included in the multivariable logistic regression analysis, we constructed models by combining the separate inflammatory indicator and other significant predictors and compared the area under the curve (AUC). A nomogram based on the PIV for PCa was developed.

RESULTS

We included 148 PCa patients (including 127 CSPCa patients) and 171 non-PCa patients in total. The patients with PCa were older, had higher MLR, SII, PIV, and total PSA (TPSA) values, consumed more alcohol, and had lower free/total PSA (f/T) values than the other patients. Compared with the non-CSPCa group, the CSPCa group had higher BMI, MLR, PIV, TPSA values, consumed more alcohol, and had lower f/T values. The univariable regression analysis showed that drinking history, higher MLR, PIV, and TPSA values, and lower f/T values were independent predictors of PCa and CSPCa. The AUC of the PIV in the multivariable logistic regression model was higher than those of the MLR and SII. In addition, the diagnostic value of the PIV + PSA for PCa was better than the PSA value. However, the diagnostic value for CSPCa was not significantly different from that of using PSA alone, while the AUC of the PIV + PSA was higher than the individual indicator of the PSA value.

CONCLUSIONS

Our study suggests that for the patients who were diagnosed with PSA values between 4 and 20 ng/mL, the PIV and MLR are potential indicators for predicting PCa and CSPCa. In addition, our study indicates that the new inflammatory index PIV has clinical value in the diagnosis of PCa and CSPCa.

摘要

引言

评估全免疫炎症值(PIV)和其他全身炎症标志物,包括中性粒细胞与淋巴细胞比值(NLR)、衍生中性粒细胞与淋巴细胞比值(dNLR)、单核细胞与淋巴细胞比值(MLR)、血小板与淋巴细胞比值(PLR)以及全身免疫炎症指数(SII),对前列腺特异性抗原(PSA)值在4至20 ng/mL之间的前列腺癌(PCa)和临床显著性前列腺癌(CSPCa)的预测价值。

患者与方法

回顾性分析了2019年8月至2022年6月在我院接受前列腺活检的319例符合条件患者的临床资料。CSPCa被定义为“Gleason分级组≥2”。进行单变量逻辑回归分析和多变量逻辑回归分析,以分析PIV、SII、MLR与PCa/CSPCa之间的关联。对于多变量逻辑回归分析中纳入的炎症指标,我们通过将单独的炎症指标与其他显著预测因素相结合构建模型,并比较曲线下面积(AUC)。开发了基于PIV的PCa列线图。

结果

我们共纳入了148例PCa患者(包括127例CSPCa患者)和171例非PCa患者。PCa患者年龄更大,MLR、SII、PIV和总PSA(TPSA)值更高,饮酒量更多,游离/总PSA(f/T)值更低。与非CSPCa组相比,CSPCa组的BMI、MLR、PIV、TPSA值更高,饮酒量更多,f/T值更低。单变量回归分析显示,饮酒史、较高的MLR、PIV和TPSA值以及较低的f/T值是PCa和CSPCa的独立预测因素。多变量逻辑回归模型中PIV的AUC高于MLR和SII。此外,PIV + PSA对PCa的诊断价值优于PSA值。然而,其对CSPCa的诊断价值与单独使用PSA相比无显著差异,而PIV + PSA的AUC高于PSA值的单个指标。

结论

我们的研究表明,对于PSA值在4至20 ng/mL之间的患者,PIV和MLR是预测PCa和CSPCa的潜在指标。此外,我们的研究表明,新的炎症指标PIV在PCa和CSPCa的诊断中具有临床价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5a9/9917630/ce1561b50f83/jcm-12-00820-g001.jpg

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