■本研究的目的是探讨血清高敏C反应蛋白/白蛋白比值在原发性前列腺活检中的临床意义。
■对2010年至2018年在我们的情况下进行首次经直肠或会阴前列腺活检的1679例患者的临床资料进行了回顾性分析。病理诊断为前列腺癌(PCa)和良性前列腺增生(BPH)的819例和860例,分别。比较了PCa和BPH患者之间的HAR差异以及HAR升高和正常组之间的前列腺活检阳性率差异。前列腺活检结果采用logistic回归分析,并建立了预测前列腺癌的模型。受试者特征曲线(ROC)用于确定模型的预测有效性。使用净重新分类改进(NRI)和综合辨别改进(IDI)评估了整合到HAR中的临床模型增加分类功效的潜力。根据格里森评分(GS)分类系统,前列腺癌患者被分成低,中间,高GS组。然后比较各组之间的HAR差异。使用卡方检验比较正常人群中高GSPCa和转移性PCa的患病率以及前列腺癌患者中高HAR的患病率。
■PCa患者的中位数HAR(上四分位数到下四分位数)为0.0379(10-3),BPH患者的中位HAR(0.0137(10-3)),差异有统计学意义(p<0.05)。HAR升高的患者和正常组,分别,前列腺活检阳性率为52%(435/839)和46%(384/840),差异有统计学意义(p<0.05)。Logistic回归分析显示HAR(OR=3.391,95CI2.082~4.977,P<0.05),PSA密度(PSAD)(OR=7.248,95CI5.005~10.495,P<0.05)和年龄(OR=1.076,95CI1.056~1.096,P<0.05)是前列腺穿刺活检结果的独立预测因子。建立了两种预测模型:基于年龄和PSAD的临床模型,以及将HAR添加到临床模型中的预测模型。两个模型的ROC曲线下面积(AUC)为0.814(95CI0.78-0.83)和0.815(95CI0.79-0.84),分别。与AUC为0.746(95CI0.718-0.774)的单一血液总PSA(tPSA)相比,他们都是优越的。然而,两种模型间差异无统计学意义(p<0.05)。我们评估了集成到HAR的能力中的预测模型,以使用NRI和IDI提高分类效率,NRI>0,IDI>0,差异有统计学意义(P>0.05)。对于由于活检而患有前列腺癌的个体,不同GS组之间的HAR存在统计学上的显著差异(p<0.05)。高GS和转移性患者的发生率在HAR升高组中有统计学意义(p<0.05)(90.1%和39.3%,分别)高于HAR正常组(84.4%和12.0%)。
■阳性的前列腺活检结果受到HAR的影响,随着PCa发现率增加的独立因素。在最近通过前列腺活检诊断为前列腺癌的患者中,HAR升高的患者发生高GS以及转移性PCa的风险更大。
UNASSIGNED: The purpose of this study was to investigate the clinical significance of serum high sensitive C-reactive protein/albumin ratio in primary prostate biopsy.
UNASSIGNED: Retrospective analysis was done on the clinical data of 1679 patients who had their first transrectal or perineal prostate biopsy at our situation from 2010 to 2018. Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) were the pathologic diagnoses in 819 and 860 cases, respectively. A comparison was made between the HAR differences between PCa and BPH patients as well as the positive prostate biopsy rate differences between groups with increased and normal HAR. The results of the prostate biopsy were examined using logistic regression, and a model for predicting prostate cancer was created. The receiver characteristic curve (ROC) was used to determine the model\'s prediction effectiveness. The clinical models integrated into HAR were evaluated for their potential to increase classification efficacy using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). According to the Gleason score (GS) categorization system, prostate cancer patients were separated into low, middle, and high GS groups. The differences in HAR between the various groups were then compared. The prevalence of high GSPCa and metastatic PCa in normal populations and the prevalence of higher HAR in prostate cancer patients were compared using the chi-square test.
UNASSIGNED: Patients with PCa had a median HAR (upper quartile to lower quartile) of 0.0379 (10-3), patients with BPH had a median HAR (0.0137 (10-3)), and the difference was statistically significant (p<0.05). Patients with increased HAR and the normal group, respectively, had positive prostate biopsy rates of 52% (435/839)and 46% (384/840), and the difference was statistically significant (p<0.05). Logistic regression analysis showed that HAR (OR=3.391, 95%CI 2.082 ~ 4.977, P < 0.05), PSA density (PSAD) (OR=7.248, 95%CI 5.005 ~ 10.495, P < 0.05) and age (OR=1.076, 95%CI 1.056 ~ 1.096, P < 0.05) was an independent predictor of prostate biopsy results. Two prediction models are built: a clinical model based on age and PSAD, and a prediction model that adds HAR to the clinical model. The two models\' ROC had area under the curves (AUC) of 0.814 (95%CI 0.78-0.83) and 0.815 (95%CI 0.79-0.84), respectively. When compared to a single blood total PSA (tPSA) with an AUC of 0.746 (95%CI 0.718-0.774), they were all superior. Nevertheless, there was no statistically significant difference (p<0.05) between the two models. We assessed the prediction model integrated into HAR\'s capacity to increase classification efficiency using NRI and IDI, and we discovered that NRI>0, IDI>0, and the difference was statistically significant (P>0.05).There was a statistically significant difference in HAR between various GS groups for individuals who had prostate cancer as a consequence of biopsy (p<0.05). The incidence of high GS and metastatic patients was statistically significantly greater (p<0.05) in the HAR elevated group (90.1%and 39.3%, respectively) than in the HAR normal group (84.4% and 12.0%).
UNASSIGNED: Prostate biopsy results that were positive were impacted by HAR, an independent factor that increased with the rate of PCa discovery. Patients with elevated HAR had a greater risk of high GS as well as metastatic PCa among those with recently diagnosed prostate cancer through prostate biopsy.