结合前列腺体积和表观弥散系数可对 PI-RADS 评分为 3 分的患者进行分层，以减少不必要的前列腺活检。

IF 2.6 3区医学 Q3 ENDOCRINOLOGY & METABOLISM Prostate Pub Date : 2024-06-01 Epub Date: 2024-04-01 DOI:10.1002/pros.24695

Qifei Dong, Changming Wang, Deyun Shen, Yifan Ma, Bin Zhang, Siqin Xu, Tao Tao, Jun Xiao

{"title":"结合前列腺体积和表观弥散系数可对 PI-RADS 评分为 3 分的患者进行分层，以减少不必要的前列腺活检。","authors":"Qifei Dong, Changming Wang, Deyun Shen, Yifan Ma, Bin Zhang, Siqin Xu, Tao Tao, Jun Xiao","doi":"10.1002/pros.24695","DOIUrl":null,"url":null,"abstract":"Background: Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies.Methods: Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables.Results: Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with \"PV < 55 mL and ADCmin < 685 μm2/s\" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 μm2/s were diagnosed with csPCa.Conclusions: In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with \"PV ≥ 55 mL and ADCmin ≥ 685 μm2/s\" may safely avoid prostate biopsies.","PeriodicalId":54544,"journal":{"name":"Prostate","volume":" ","pages":"780-787"},"PeriodicalIF":2.6000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies.\",\"authors\":\"Qifei Dong, Changming Wang, Deyun Shen, Yifan Ma, Bin Zhang, Siqin Xu, Tao Tao, Jun Xiao\",\"doi\":\"10.1002/pros.24695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies.Methods: Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables.Results: Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with \\\"PV < 55 mL and ADCmin < 685 μm2/s\\\" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 μm2/s were diagnosed with csPCa.Conclusions: In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with \\\"PV ≥ 55 mL and ADCmin ≥ 685 μm2/s\\\" may safely avoid prostate biopsies.\",\"PeriodicalId\":54544,\"journal\":{\"name\":\"Prostate\",\"volume\":\" \",\"pages\":\"780-787\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Prostate\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/pros.24695\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/4/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Prostate","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/pros.24695","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/1 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}

引用次数: 0

摘要

背景：我们的目的是确定前列腺体积（PV）和最小表观弥散系数（ADCmin）的临界值，对这些患者进行分层，以减少不必要的前列腺活检：收集2019年1月至2023年6月期间接受前列腺活检的224名合格患者的数据。采用 Mann-Whitney U 检验比较非正态分布的连续变量，以中位数（四分位数间距）记录。相关系数采用斯皮尔曼等级相关分析法计算。分类变量以数字（百分比）记录，并通过 χ2 检验进行比较。单变量和多变量逻辑回归分析用于确定独立的预测因素。接受者操作特征曲线和曲线下面积（AUC）用于评估临床变量的诊断性能：在总共 224 名患者中，36 名患者（16.07%）被诊断为有临床意义的前列腺癌（csPCa），72 名患者（32.14%）被诊断为任何级别的前列腺癌。多变量分析结果显示，诊断 csPCa 的 PV 和 p min 分别为 0.779（95% CI：0.718-0.831）和 0.799（95% CI：0.740-0.849）。根据 PV 和 ADCmin 对患者进行分层后，有 24 例（47.06%）"PV min 2/s "的患者被诊断为 csPCa。然而，只有一名 PV ≥ 55 mL 且 ADCmin ≥ 685 μm2/s 的患者（1.25%）被诊断为 csPCa：在这项研究中，我们发现结合 PV 和 ADCmin 可以对 PI-RADS 评分为 3 分的患者进行分层，从而减少不必要的前列腺活检。这些 "PV ≥ 55 mL 和 ADCmin ≥ 685 μm2/s "的患者可以安全地避免前列腺活检。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies.

Background: Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADC_min) to stratify those patients to reduce unnecessary prostate biopsies.

Methods: Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ² test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables.

Results: Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADC_min (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADC_min were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADC_min, 24 patients (47.06%) with "PV < 55 mL and ADC_min < 685 μm²/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADC_min ≥ 685 μm²/s were diagnosed with csPCa.

Conclusions: In this study, we found the combination of PV and ADC_min can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADC_min ≥ 685 μm²/s" may safely avoid prostate biopsies.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Prostate 医学-泌尿学与肾脏学

CiteScore

5.10

自引率

3.60%

发文量

180

审稿时长

1.5 months

期刊介绍： The Prostate is a peer-reviewed journal dedicated to original studies of this organ and the male accessory glands. It serves as an international medium for these studies, presenting comprehensive coverage of clinical, anatomic, embryologic, physiologic, endocrinologic, and biochemical studies.