The overdiagnosis of prostate cancer(PCa)caused by nonspecific elevation serum prostate-specific antigen(PSA)and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently.We aimed...The overdiagnosis of prostate cancer(PCa)caused by nonspecific elevation serum prostate-specific antigen(PSA)and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently.We aimed to construct a prediction model and provide a risk stratification system to reduce unnecessary biopsies.In this retrospective study,clinical data of 1807 patients from three Chinese hospitals were used.The final model was built using stepwise logistic regression analysis.The apparent performance of the model was assessed by receiver operating characteristic curves,calibration plots,and decision curve analysis.Finally,a risk stratification system of clinically significant prostate cancer(csPCa)was created,and diagnosis-free survival analyses were performed.Following multivariable screening and evaluation of the diagnostic performances,a final diagnostic model comprised of the PSA density and Prostate Imaging-Reporting and Data System(PI-RADS)score was established.Model validation in the development cohort and two external cohorts showed excellent discrimination and calibration.Finally,we created a risk stratification system using risk thresholds of 0.05 and 0.60 as the cut-off values.The follow-up results indicated that the diagnosis-free survival rate for csPCa at 12 months and 24 months postoperatively was 99.7%and 99.4%,respectively,for patients with a risk threshold below O.05 after the initial negative prostate biopsy,which was significantly better than patients with higher risk.Our diagnostic model and risk stratification system can achieve a personalized risk calculation of csPCa.It provides a standardized tool for Chinese patients and physicians when considering thenecessity of prostatebiopsy.展开更多
Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with P...Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with PCa, clinically significant PCa （CSPCa）, or no PCa, especially among those with serum total prostate-specific antigen （tPSA） levels in the ＂gray zone＂ （4-10 ng ml-1）. A total of 308 patients （355 lesions） were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density （PSAD） were independent predictors of PCa and CSPCa. A PI-RADS v2 score L≥4 provided high negative predictive values （91.39% for PCa and 95.69% for CSPCa）. A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group （PI-RADS score = 5 and PSAD L≥0 15 ng ml-1 cm-3, with tPSA in the gray zone, or PI-RADS score L≥4 with high tPSA level） with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.展开更多
BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 ...BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 and 385 patients,respectively),but their results are discordant.AIM To synthetize the available evidence on the effectiveness of lutetium in pre-treated metastatic castration-resistant prostate cancer;and to test the application of a new artificial intelligence technique that synthetizes effectiveness based on reconstructed patient-level data.METHODS We employed a new artificial intelligence method(shiny method)to pool the survival data of these two trials and evaluate to what extent the lutetium cohorts differed from one another.The shiny technique employs an original reconstruction of individual patient data from the Kaplan-Meier curves.The progression-free survival graphs of the two lutetium cohorts were analyzed and compared.RESULTS The hazard ratio estimated was in favor of the vision trial;the difference was statistically significant(P<0.001).These results indicate that further studies on lutetium are needed because the survival data of the two trials published thus far are conflicting.CONCLUSION Our study confirms the feasibility of reconstructing patient-level data from survival graphs in order to generate a survival statistics.展开更多
Objective: Excavate the medication rule of traditional Chinese medicine in the treatment of prostate cancer, and predicting the biomolecular level mechanism of high-frequency drug compatibility. Methods: Relevant docu...Objective: Excavate the medication rule of traditional Chinese medicine in the treatment of prostate cancer, and predicting the biomolecular level mechanism of high-frequency drug compatibility. Methods: Relevant documents in CNKI, Wanfang Medical Network and VIP Chinese Biomedical Periodical Database Pubmed, EMbase were collected and collated systematically. Frequency statistics, association rule analysis and new party mining were carried out using TCMISSV2.5. BATMAN-TCM was used to analyze the interaction relationship and related pathways between high-frequency drug targets. Results: Huangqi (Astragalus membranaceus) was the single drug most used of the 102prescriptions included in the standard. There are 6 pairs of combinations with high confidence in association rule analysis. System entropy cluster analysis resulted in 20 core drug combinations and 9 new prescriptions. Through KEGG pathway analysis of Huangqi, Fuling (Poria cocos), Gancao (Glycyrrhiza uralensis) and Dihuang (Rehmannia glutinosa), it was found that the number of potential targets of the neural active ligand receptor rented pathway and purine metabolism pathway was the largest. Conclusions: Prostate cancer is mainly treated with deficiency-tonifying drugs, which are combined with drugs for promoting blood circulation, removing blood stasis, clearing heat, promoting diuresis, detoxifying and resolving hard mass. The mechanism of action of high-frequency traditional Chinese medicine may be realized by interfering with the neuroactive ligand receptor interaction pathway and purine metabolism pathway.展开更多
Objective To measure the intraobserver concordance of an experienced genitourinary radiologist reporting of multiparametric magnetic resonance imaging of the prostate(mpMRIp)scans over time.Methods An experienced geni...Objective To measure the intraobserver concordance of an experienced genitourinary radiologist reporting of multiparametric magnetic resonance imaging of the prostate(mpMRIp)scans over time.Methods An experienced genitourinary radiologist re-reported his original 100 consecutive mpMRIp scans using Prostate Imaging-Reporting and Data System version 2(PI-RADS v2)after 5 years of further experience comprising>1000 scans.Intraobserver agreement was measured using Cohen's kappa.Sensitivity,specificity,negative predictive value(NPV),positive predictive value(PPV),and accuracy were calculated,and comparison of sensitivity was performed using McNemar's test.Results Ninety-six mpMRIp scans were included in our final analysis.Of the 96 patients,53(55.2%)patients underwent subsequent biopsy(n=43)or prostatectomy(n=15),with 73 lesions targeted.Moderate agreement(Cohen's kappa 0.55)was seen in the number of lesions identified at initial reporting and on re-reading(81 vs.39 total lesions;and 71 vs.37 number of PI-RADS≥3 lesions).For clinically significant prostate cancer,re-reading demonstrated an increase in specificity(from 43%to 89%)and PPV(from 62%to 87%),but a decrease in sensitivity(from 94%to 72%,p=0.01)and NPV(from 89%to 77%).Conclusion The intraobserver agreement for a novice to experienced radiologist reporting mpMRIp using PI-RADS v2 is moderate.Reduced sensitivity is off-set by improved specificity and PPV,which validate mpMRIp as a gold standard for prebiopsy screening.展开更多
This study explored a new model of Prostate Imaging Reporting and Data System(PIRADS)and adjusted prostate-specific antigen density of peripheral zone(aPSADPZ)for predicting the occurrence of prostate cancer(PCa)and c...This study explored a new model of Prostate Imaging Reporting and Data System(PIRADS)and adjusted prostate-specific antigen density of peripheral zone(aPSADPZ)for predicting the occurrence of prostate cancer(PCa)and clinically significant prostate cancer(csPCa).The demographic and clinical characteristics of 853 patients were recorded.Prostate-specific antigen(PSA),PSA density(PSAD),PSAD of peripheral zone(PSADPZ),aPSADPZ,and peripheral zone volume ratio(PZ-ratio)were calculated and subjected to receiver operating characteristic(ROC)curve analysis.The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve(AUC).The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves.The AUCs of PSA,PSAD,PSADPZ,aPSADPZ,and PZ-ratio were 0.669,0.762,0.659,0.812,and 0.748 for PCa diagnosis,while 0.713,0.788,0.694,0.828,and 0.735 for csPCa diagnosis,respectively.All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa.The new model significantly improved the diagnostic accuracy of PCa(0.945 vs 0.830,P<0.01)and csPCa(0.937 vs 0.845,P<0.01)compared with the base model.In addition,the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold.This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators.Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.展开更多
Introduction and Objective: Prostate cancer detection is a difficult process despite different modalities that are available. The current standard of practice is based on stratifying risk using Prostate Specific Antig...Introduction and Objective: Prostate cancer detection is a difficult process despite different modalities that are available. The current standard of practice is based on stratifying risk using Prostate Specific Antigen (PSA), digital rectal examination (DRE) and performing a transrectal ultrasound (TRUS) or transperineal (TP) guided biopsy. Recent advances in three-tesla multiparametric magnetic resonance imaging (MP-MRI) technology and the availability of in-gantry MRI guided biopsies (MRGB) have added another diagnostic tool in management of prostate cancer. We review MRGB performed on high Prostate Imaging Reporting and Data System (PIRADS) score lesions in a single centre retrospective study. Materials and Methods: There were 77 patients (mean age 63) with high PIRADS score (4 and 5) that underwent in-gantry MRGB. All the biopsies were performed utilizing dynacad prostate biopsy system on a three-tesla MRI scanner by an urologist with assistance of an experienced radiologist. Two to three samples were obtained from each lesion using an MRI compatible 18-gauge biopsy needle. Three experienced pathologists evaluated the samples and provided the results and Gleason score in each positive sample. Results: Out of the total 77 high PIRADS patients, 54 were PIRADS score 4 (70%) and 23 PIRADS score 5 (30%). There were 22 positive biopsies for adenocarcinoma of prostate with a Gleason score of 3 + 3 = 6 or higher. Out of the 54 PIRADS score 4 lesions, 13 were positive (24%) and out of 23 PIRADS 5 lesions, 9 were positive (39%). The remaining 55 biopsies were negative for prostate cancer. Conclusion: We present our series of MRGB in patients with a high PIRADS score for prostate cancer. While this diagnostic paradigm was in its infancy stages, MRGB was positive in 24% of PIRADS 4 and 39% of PIRADS 5 lesions in this series.展开更多
目的 探讨表观扩散系数平均值(mean apparent diffusion coefficient,ADCmean)联合前列腺特异性抗原密度(prostate specific antigen density,PSAD)对前列腺影像报告和数据系统(prostate imaging reporting and data system,PI-RADS)≥...目的 探讨表观扩散系数平均值(mean apparent diffusion coefficient,ADCmean)联合前列腺特异性抗原密度(prostate specific antigen density,PSAD)对前列腺影像报告和数据系统(prostate imaging reporting and data system,PI-RADS)≥3分临床显著性前列腺癌(clinical significant prostate cancer,csPCa)的预测价值。材料与方法 回顾性分析2022年2月至2024年8月期间我院行前列腺MRI检查PI-RADS评分≥3分且有病理组织学检查患者的临床资料和影像资料。选择最高PI-RADS评分且最大病灶的最大层面勾画感兴趣区(region of interest,ROI),测量病灶的ADCmean和表观扩散系数最小值(min apparent diffusion coefficient,ADCmin)。单因素和多因素logistic回归分析筛选出预测csPCa的最佳临床和影像指标,采用受试者工作特征(receiver operating characteristics,ROC)曲线比较最佳临床和影像预测模型及两者联合模型的诊断效能,计算曲线下面积(area under the curve,AUC)、敏感度和特异度,并行DeLong检验。结果 本研究共纳入csPCa患者75例(48.39%),非csPCa患者80例(51.61%)。csPCa组的年龄、总前列腺特异性抗原(total prostate specific antigen,tPSA)、游离前列腺特异性抗原(free prostate specific antigen,fPSA)、PSAD大于非csPCa组,csPCa组的前列腺体积(prostate volume,PV)、fPSA和tPSA比值(f/t)、ADCmin、ADCmean均小于非csPCa组,差异具有统计学意义(均P<0.05)。逐步logistic回归筛选和ROC曲线分析,获得预测csPCa的最佳临床指标为PSAD和影像指标ADCmean,AUC分别为0.846、0.898,PSAD诊断阈值为0.307 ng/mL2,敏感度为66.67%,特异度为91.25%,ADCmean诊断阈值为773.5 mm2/s,敏感度为86.67%,特异度为85.00%,两者联合模型的AUC高达0.925。DeLong检验比较联合模型与单一模型的AUC差异有统计学意义(P<0.05),联合模型预测csPCa的敏感性和特异度分别为86.67%和88.75%。结论 ADCmean对PI-RADS≥3分csPCa的预测效能优于ADCmin,与PSAD的联合模型能进一步提高对PI-RADS≥3分csPCa的预测价值,对临床诊疗具有指导意义。展开更多
Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American C...Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American College of Radiology revised the PI-RADS to address the limitations of version 1 in December 2014.This study aimed to determine whether the PI-RADS version 2 （PI-RADS v2） scoring system improves the diagnostic accuracy of mp-MRI of the prostate compared with PI-RADS v1.Methods：This retrospective study was approved by the institutional review board.A total of 401 consecutive patients,with clinically suspicious Pca undergoing 3.0 T mp-MRI （T2-weighted imaging ＋ diffusion-weighted imaging ＋ DCE） before transrectal ultrasound-guided biopsy between June 2013 and July 2015,were included in the study.All patients were scored using the 5-point PI-RADS scoring system based on either PI-RADS v1 or v2.Receiver operating characteristics were calculated for statistical analysis.Sensitivity,specificity,and diagnostic accuracy were compared using McNemar＇s test.Results：Pca was present in 150 of 401 （37.41%） patients.When we pooled data from both peripheral zone （PZ） and transition zone （TZ）,the areas under the curve were 0.889 for PI-RADS v1 and 0.942 for v2 （P =0.0001）.Maximal accuracy was achieved with a score threshold of 4.At this threshold,in the PZ,similar sensitivity,specificity,and accuracy were achieved with v 1 and v2 （all P 〉 0.05）.In the TZ,sensitivity was higher for v2 than for v1 （96.36% vs.76.36%,P =0.003）,specificity was similar for v2 and v1 （90.24% vs.84.15%,P =0.227）,and accuracy was higher for v2 than for v1 （92.70% vs.81.02%,P =0.002）.Conclusions：Both v1 and v2 showed good diagnostic performance for the detection of Pca.However,in the TZ,the performance was better with v2 than with v1.展开更多
Background： The European Society of Urogenital Radiology has built the Prostate Imaging Reporting and Data System （PI-RADS） for standardizing the diagnosis of prostate cancer （PCa）. This study evaluated the PI-RA...Background： The European Society of Urogenital Radiology has built the Prostate Imaging Reporting and Data System （PI-RADS） for standardizing the diagnosis of prostate cancer （PCa）. This study evaluated the PI-RADS diagnosis method in patients with prostate-specific antigen （PSA） 〈20 ng/ml. Methods： A total of 133 patients with PSA 〈20 ng/ml were prospectively recruited. T2-weighted （T2WI） and diffusion-weighted （DWI） magnetic resonance images of the prostate were acquired before a 12-core transrectal prostate biopsy. Each patient＇s peripheral zone was divided into six regions on the images; each region corresponded to two of the 12 biopsy cores. T2WI, DWI, and T2W1 ＋ DWI scores were computed according to PI-RADS. The diagnostic accuracy of the PI-RADS score was evaluated using histopathology of prostate biopsies as the reference standard. Results： PCa was histologically diagnosed in 169 （21.2%） regions. Increased PI-RADS score correlated positively with increased cancer detection rate. The cancer detection rate for scores 1 to 5 was 2.8%, 15.0%, 34.6%, 52.6%, and 88.9%, respectively, using T2W1 and 12.0%, 20.2%, 48.0%, 85.7%, and 93.3%, respectively, using DWI. For T2WI ＋ DWI, the cancer detection rate was 1.5% （score 2）, 13.5% （scores 3-4）, 41.3% （scores 5-6）, 75.9% （scores 7-8）, and 92.3% （scores 9-10）. The area under the curve for cancer detection was 0.700 （T2WI）, 0.735 （DWI） and 0.749 （T2WI ＋ DWI）. The sensitivity and specificity were 53.8% and 89.2%, respectively, when The summed score ofT2Wl ＋ DWI展开更多
目的探讨基于双参数磁共振成像(biparametric magnetic resonance imaging,bp-MRI)的前列腺影像报告和数据系统2.1版(prostate imaging report and data system version 2.1,PI-RADS v2.1)联合前列腺特异性抗原密度(prostate specific a...目的探讨基于双参数磁共振成像(biparametric magnetic resonance imaging,bp-MRI)的前列腺影像报告和数据系统2.1版(prostate imaging report and data system version 2.1,PI-RADS v2.1)联合前列腺特异性抗原密度(prostate specific antigen density,PSAD)鉴别诊断总前列腺特异性抗原(total prostate specific antigen,tPSA)4~20 ng/mL临床显著性前列腺癌(clinically significant prostate cancer,csPCa)的价值及风险分层。材料与方法回顾性分析了宁夏医科大学总医院2017年10月至2023年6月304例PSA 4~20 ng/mL前列腺疾病患者的bp-MRI图像和临床资料。根据病理结果分为csPCa组(Gleason评分≥7分,n=66)和非csPCa(Gleason评分<7分及良性疾病,n=238)。经单因素、多因素logistic回归分析筛选独立危险因子并建立联合模型,再用决策曲线分析(decision curve analysis,DCA)其临床净效益。以受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under the curve,AUC)比较独立危险因子与联合模型的诊断效能,并对独立危险因子进行等级划分和组合。结果联合模型(PI-RADS v2.1+PSAD)的诊断效能最好(AUC为0.901,95%CI:0.858~0.944)。将PI-RADS v2.1与PSAD等级划分并组合,当PI-RADS v2.1≤2且PSAD≤0.15 ng/mL^(2),csPCa阳性率为0%;当PI-RADS v2.1为3分且PSAD<0.30 ng/mL^(2)时,csPCa阳性率<15%;当PI-RADS v2.1为4~5分且PSAD为0.15~0.29 ng/mL^(2)时,csPCa阳性率为46.5%;当PI-RADS v2.1为4~5分且PSAD≥0.30 ng/mL^(2)时,csPCa阳性率高达81.3%。结论PI-RAD v2.1≤2或PI-RAD v2.1=3且PSAD值<0.30 ng/ml2的患者可避免不必要的活检。PI-RADS v2.1联合PSAD能显著提高tPSA 4~20 ng/mL csPCa的诊断效能,将二者联合有助于穿刺前对csPCa的患者进行风险评估,以减少部分患者不必要的穿刺,并为临床提供一定的决策指导。展开更多
前列腺癌(prostate cancer,PCa)的早期诊断对其预后至关重要,前列腺特异性抗原是PCa筛查最重要的肿瘤标志物,但其诊断仍需联合影像学及病理结果。前列腺影像报告和数据系统(prostate imaging report and data system,PI-RADS)是基于多...前列腺癌(prostate cancer,PCa)的早期诊断对其预后至关重要,前列腺特异性抗原是PCa筛查最重要的肿瘤标志物,但其诊断仍需联合影像学及病理结果。前列腺影像报告和数据系统(prostate imaging report and data system,PI-RADS)是基于多参数核磁共振成像的前列腺癌风险评估系统,目前已经更新至PI-RADS v2.1。PI-RADS v2.1评分在PCa早期诊断中发挥了重要作用,但也存在一些不足。本文旨在全面概述PI-RADS v2.1评分在PCa诊断中的作用,并分析其不足和应用前景。展开更多
基金This study was supported by the Key Research and Development Program of Anhui Province(No.202204295107020003)the National Natural Science Foundation of Anhui Province(No.2108085MH293)+1 种基金the Distinguished Young Scholars Fund of Anhui Province(No.2022AH020078)the Key health Project of Anhui Province(AHWJ2022a037).
文摘The overdiagnosis of prostate cancer(PCa)caused by nonspecific elevation serum prostate-specific antigen(PSA)and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently.We aimed to construct a prediction model and provide a risk stratification system to reduce unnecessary biopsies.In this retrospective study,clinical data of 1807 patients from three Chinese hospitals were used.The final model was built using stepwise logistic regression analysis.The apparent performance of the model was assessed by receiver operating characteristic curves,calibration plots,and decision curve analysis.Finally,a risk stratification system of clinically significant prostate cancer(csPCa)was created,and diagnosis-free survival analyses were performed.Following multivariable screening and evaluation of the diagnostic performances,a final diagnostic model comprised of the PSA density and Prostate Imaging-Reporting and Data System(PI-RADS)score was established.Model validation in the development cohort and two external cohorts showed excellent discrimination and calibration.Finally,we created a risk stratification system using risk thresholds of 0.05 and 0.60 as the cut-off values.The follow-up results indicated that the diagnosis-free survival rate for csPCa at 12 months and 24 months postoperatively was 99.7%and 99.4%,respectively,for patients with a risk threshold below O.05 after the initial negative prostate biopsy,which was significantly better than patients with higher risk.Our diagnostic model and risk stratification system can achieve a personalized risk calculation of csPCa.It provides a standardized tool for Chinese patients and physicians when considering thenecessity of prostatebiopsy.
文摘Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with PCa, clinically significant PCa （CSPCa）, or no PCa, especially among those with serum total prostate-specific antigen （tPSA） levels in the ＂gray zone＂ （4-10 ng ml-1）. A total of 308 patients （355 lesions） were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density （PSAD） were independent predictors of PCa and CSPCa. A PI-RADS v2 score L≥4 provided high negative predictive values （91.39% for PCa and 95.69% for CSPCa）. A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group （PI-RADS score = 5 and PSAD L≥0 15 ng ml-1 cm-3, with tPSA in the gray zone, or PI-RADS score L≥4 with high tPSA level） with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.
文摘BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 and 385 patients,respectively),but their results are discordant.AIM To synthetize the available evidence on the effectiveness of lutetium in pre-treated metastatic castration-resistant prostate cancer;and to test the application of a new artificial intelligence technique that synthetizes effectiveness based on reconstructed patient-level data.METHODS We employed a new artificial intelligence method(shiny method)to pool the survival data of these two trials and evaluate to what extent the lutetium cohorts differed from one another.The shiny technique employs an original reconstruction of individual patient data from the Kaplan-Meier curves.The progression-free survival graphs of the two lutetium cohorts were analyzed and compared.RESULTS The hazard ratio estimated was in favor of the vision trial;the difference was statistically significant(P<0.001).These results indicate that further studies on lutetium are needed because the survival data of the two trials published thus far are conflicting.CONCLUSION Our study confirms the feasibility of reconstructing patient-level data from survival graphs in order to generate a survival statistics.
基金the National Natural Science Foundation of Hebei (No.H2018201179)Hebei University of Science and Technology (No. QN2016077)Health and Family Planning Commission of Hebei (No. 20160388).
文摘Objective: Excavate the medication rule of traditional Chinese medicine in the treatment of prostate cancer, and predicting the biomolecular level mechanism of high-frequency drug compatibility. Methods: Relevant documents in CNKI, Wanfang Medical Network and VIP Chinese Biomedical Periodical Database Pubmed, EMbase were collected and collated systematically. Frequency statistics, association rule analysis and new party mining were carried out using TCMISSV2.5. BATMAN-TCM was used to analyze the interaction relationship and related pathways between high-frequency drug targets. Results: Huangqi (Astragalus membranaceus) was the single drug most used of the 102prescriptions included in the standard. There are 6 pairs of combinations with high confidence in association rule analysis. System entropy cluster analysis resulted in 20 core drug combinations and 9 new prescriptions. Through KEGG pathway analysis of Huangqi, Fuling (Poria cocos), Gancao (Glycyrrhiza uralensis) and Dihuang (Rehmannia glutinosa), it was found that the number of potential targets of the neural active ligand receptor rented pathway and purine metabolism pathway was the largest. Conclusions: Prostate cancer is mainly treated with deficiency-tonifying drugs, which are combined with drugs for promoting blood circulation, removing blood stasis, clearing heat, promoting diuresis, detoxifying and resolving hard mass. The mechanism of action of high-frequency traditional Chinese medicine may be realized by interfering with the neuroactive ligand receptor interaction pathway and purine metabolism pathway.
基金This research has been kindly supported by a grant from the St Vincent's Research Endowment Fund(approval number 55.2014).
文摘Objective To measure the intraobserver concordance of an experienced genitourinary radiologist reporting of multiparametric magnetic resonance imaging of the prostate(mpMRIp)scans over time.Methods An experienced genitourinary radiologist re-reported his original 100 consecutive mpMRIp scans using Prostate Imaging-Reporting and Data System version 2(PI-RADS v2)after 5 years of further experience comprising>1000 scans.Intraobserver agreement was measured using Cohen's kappa.Sensitivity,specificity,negative predictive value(NPV),positive predictive value(PPV),and accuracy were calculated,and comparison of sensitivity was performed using McNemar's test.Results Ninety-six mpMRIp scans were included in our final analysis.Of the 96 patients,53(55.2%)patients underwent subsequent biopsy(n=43)or prostatectomy(n=15),with 73 lesions targeted.Moderate agreement(Cohen's kappa 0.55)was seen in the number of lesions identified at initial reporting and on re-reading(81 vs.39 total lesions;and 71 vs.37 number of PI-RADS≥3 lesions).For clinically significant prostate cancer,re-reading demonstrated an increase in specificity(from 43%to 89%)and PPV(from 62%to 87%),but a decrease in sensitivity(from 94%to 72%,p=0.01)and NPV(from 89%to 77%).Conclusion The intraobserver agreement for a novice to experienced radiologist reporting mpMRIp using PI-RADS v2 is moderate.Reduced sensitivity is off-set by improved specificity and PPV,which validate mpMRIp as a gold standard for prebiopsy screening.
基金supported by two grants from the Key Research and Development Program of jiangsu Province (No.BE2020654 and No.BE2020655)a grant from the General Program of Jiangsu Health Commission (No.H2019040)a grant from National Key R&D Program of China (No.2017YFC0114303).
文摘This study explored a new model of Prostate Imaging Reporting and Data System(PIRADS)and adjusted prostate-specific antigen density of peripheral zone(aPSADPZ)for predicting the occurrence of prostate cancer(PCa)and clinically significant prostate cancer(csPCa).The demographic and clinical characteristics of 853 patients were recorded.Prostate-specific antigen(PSA),PSA density(PSAD),PSAD of peripheral zone(PSADPZ),aPSADPZ,and peripheral zone volume ratio(PZ-ratio)were calculated and subjected to receiver operating characteristic(ROC)curve analysis.The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve(AUC).The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves.The AUCs of PSA,PSAD,PSADPZ,aPSADPZ,and PZ-ratio were 0.669,0.762,0.659,0.812,and 0.748 for PCa diagnosis,while 0.713,0.788,0.694,0.828,and 0.735 for csPCa diagnosis,respectively.All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa.The new model significantly improved the diagnostic accuracy of PCa(0.945 vs 0.830,P<0.01)and csPCa(0.937 vs 0.845,P<0.01)compared with the base model.In addition,the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold.This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators.Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.
文摘Introduction and Objective: Prostate cancer detection is a difficult process despite different modalities that are available. The current standard of practice is based on stratifying risk using Prostate Specific Antigen (PSA), digital rectal examination (DRE) and performing a transrectal ultrasound (TRUS) or transperineal (TP) guided biopsy. Recent advances in three-tesla multiparametric magnetic resonance imaging (MP-MRI) technology and the availability of in-gantry MRI guided biopsies (MRGB) have added another diagnostic tool in management of prostate cancer. We review MRGB performed on high Prostate Imaging Reporting and Data System (PIRADS) score lesions in a single centre retrospective study. Materials and Methods: There were 77 patients (mean age 63) with high PIRADS score (4 and 5) that underwent in-gantry MRGB. All the biopsies were performed utilizing dynacad prostate biopsy system on a three-tesla MRI scanner by an urologist with assistance of an experienced radiologist. Two to three samples were obtained from each lesion using an MRI compatible 18-gauge biopsy needle. Three experienced pathologists evaluated the samples and provided the results and Gleason score in each positive sample. Results: Out of the total 77 high PIRADS patients, 54 were PIRADS score 4 (70%) and 23 PIRADS score 5 (30%). There were 22 positive biopsies for adenocarcinoma of prostate with a Gleason score of 3 + 3 = 6 or higher. Out of the 54 PIRADS score 4 lesions, 13 were positive (24%) and out of 23 PIRADS 5 lesions, 9 were positive (39%). The remaining 55 biopsies were negative for prostate cancer. Conclusion: We present our series of MRGB in patients with a high PIRADS score for prostate cancer. While this diagnostic paradigm was in its infancy stages, MRGB was positive in 24% of PIRADS 4 and 39% of PIRADS 5 lesions in this series.
文摘目的 探讨表观扩散系数平均值(mean apparent diffusion coefficient,ADCmean)联合前列腺特异性抗原密度(prostate specific antigen density,PSAD)对前列腺影像报告和数据系统(prostate imaging reporting and data system,PI-RADS)≥3分临床显著性前列腺癌(clinical significant prostate cancer,csPCa)的预测价值。材料与方法 回顾性分析2022年2月至2024年8月期间我院行前列腺MRI检查PI-RADS评分≥3分且有病理组织学检查患者的临床资料和影像资料。选择最高PI-RADS评分且最大病灶的最大层面勾画感兴趣区(region of interest,ROI),测量病灶的ADCmean和表观扩散系数最小值(min apparent diffusion coefficient,ADCmin)。单因素和多因素logistic回归分析筛选出预测csPCa的最佳临床和影像指标,采用受试者工作特征(receiver operating characteristics,ROC)曲线比较最佳临床和影像预测模型及两者联合模型的诊断效能,计算曲线下面积(area under the curve,AUC)、敏感度和特异度,并行DeLong检验。结果 本研究共纳入csPCa患者75例(48.39%),非csPCa患者80例(51.61%)。csPCa组的年龄、总前列腺特异性抗原(total prostate specific antigen,tPSA)、游离前列腺特异性抗原(free prostate specific antigen,fPSA)、PSAD大于非csPCa组,csPCa组的前列腺体积(prostate volume,PV)、fPSA和tPSA比值(f/t)、ADCmin、ADCmean均小于非csPCa组,差异具有统计学意义(均P<0.05)。逐步logistic回归筛选和ROC曲线分析,获得预测csPCa的最佳临床指标为PSAD和影像指标ADCmean,AUC分别为0.846、0.898,PSAD诊断阈值为0.307 ng/mL2,敏感度为66.67%,特异度为91.25%,ADCmean诊断阈值为773.5 mm2/s,敏感度为86.67%,特异度为85.00%,两者联合模型的AUC高达0.925。DeLong检验比较联合模型与单一模型的AUC差异有统计学意义(P<0.05),联合模型预测csPCa的敏感性和特异度分别为86.67%和88.75%。结论 ADCmean对PI-RADS≥3分csPCa的预测效能优于ADCmin,与PSAD的联合模型能进一步提高对PI-RADS≥3分csPCa的预测价值,对临床诊疗具有指导意义。
基金This study was supported by a grant of National Natural Science Foundation of China （No. 81171307）.
文摘Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American College of Radiology revised the PI-RADS to address the limitations of version 1 in December 2014.This study aimed to determine whether the PI-RADS version 2 （PI-RADS v2） scoring system improves the diagnostic accuracy of mp-MRI of the prostate compared with PI-RADS v1.Methods：This retrospective study was approved by the institutional review board.A total of 401 consecutive patients,with clinically suspicious Pca undergoing 3.0 T mp-MRI （T2-weighted imaging ＋ diffusion-weighted imaging ＋ DCE） before transrectal ultrasound-guided biopsy between June 2013 and July 2015,were included in the study.All patients were scored using the 5-point PI-RADS scoring system based on either PI-RADS v1 or v2.Receiver operating characteristics were calculated for statistical analysis.Sensitivity,specificity,and diagnostic accuracy were compared using McNemar＇s test.Results：Pca was present in 150 of 401 （37.41%） patients.When we pooled data from both peripheral zone （PZ） and transition zone （TZ）,the areas under the curve were 0.889 for PI-RADS v1 and 0.942 for v2 （P =0.0001）.Maximal accuracy was achieved with a score threshold of 4.At this threshold,in the PZ,similar sensitivity,specificity,and accuracy were achieved with v 1 and v2 （all P 〉 0.05）.In the TZ,sensitivity was higher for v2 than for v1 （96.36% vs.76.36%,P =0.003）,specificity was similar for v2 and v1 （90.24% vs.84.15%,P =0.227）,and accuracy was higher for v2 than for v1 （92.70% vs.81.02%,P =0.002）.Conclusions：Both v1 and v2 showed good diagnostic performance for the detection of Pca.However,in the TZ,the performance was better with v2 than with v1.
文摘Background： The European Society of Urogenital Radiology has built the Prostate Imaging Reporting and Data System （PI-RADS） for standardizing the diagnosis of prostate cancer （PCa）. This study evaluated the PI-RADS diagnosis method in patients with prostate-specific antigen （PSA） 〈20 ng/ml. Methods： A total of 133 patients with PSA 〈20 ng/ml were prospectively recruited. T2-weighted （T2WI） and diffusion-weighted （DWI） magnetic resonance images of the prostate were acquired before a 12-core transrectal prostate biopsy. Each patient＇s peripheral zone was divided into six regions on the images; each region corresponded to two of the 12 biopsy cores. T2WI, DWI, and T2W1 ＋ DWI scores were computed according to PI-RADS. The diagnostic accuracy of the PI-RADS score was evaluated using histopathology of prostate biopsies as the reference standard. Results： PCa was histologically diagnosed in 169 （21.2%） regions. Increased PI-RADS score correlated positively with increased cancer detection rate. The cancer detection rate for scores 1 to 5 was 2.8%, 15.0%, 34.6%, 52.6%, and 88.9%, respectively, using T2W1 and 12.0%, 20.2%, 48.0%, 85.7%, and 93.3%, respectively, using DWI. For T2WI ＋ DWI, the cancer detection rate was 1.5% （score 2）, 13.5% （scores 3-4）, 41.3% （scores 5-6）, 75.9% （scores 7-8）, and 92.3% （scores 9-10）. The area under the curve for cancer detection was 0.700 （T2WI）, 0.735 （DWI） and 0.749 （T2WI ＋ DWI）. The sensitivity and specificity were 53.8% and 89.2%, respectively, when The summed score ofT2Wl ＋ DWI
文摘前列腺癌(prostate cancer,PCa)的早期诊断对其预后至关重要,前列腺特异性抗原是PCa筛查最重要的肿瘤标志物,但其诊断仍需联合影像学及病理结果。前列腺影像报告和数据系统(prostate imaging report and data system,PI-RADS)是基于多参数核磁共振成像的前列腺癌风险评估系统,目前已经更新至PI-RADS v2.1。PI-RADS v2.1评分在PCa早期诊断中发挥了重要作用,但也存在一些不足。本文旨在全面概述PI-RADS v2.1评分在PCa诊断中的作用,并分析其不足和应用前景。
