Multi-institutional analysis of clinical and imaging risk factors for detecting clinically significant prostate cancer in men with PI-RADS 3 lesions

被引:25
作者
Fang, Andrew M. [1 ]
Shumaker, Luke A. [1 ]
Martin, Kimberly D. [2 ]
Jackson, Jamaal C. [3 ]
Fan, Richard E. [4 ]
Khajir, Ghazal [5 ]
Patel, Hiten D. [6 ]
Soodana-Prakash, Nachiketh [7 ]
Vourganti, Srinivas [3 ]
Filson, Christopher P. [8 ,9 ]
Sonn, Geoffrey A. [4 ]
Sprenkle, Preston C. [5 ]
Gupta, Gopal N. [6 ,10 ]
Punnen, Sanoj [7 ]
Rais-Bahrami, Soroush [1 ,11 ,12 ]
机构
[1] Univ Alabama Birmingham, Dept Urol, FOT 1107,510 20th St S, Birmingham, AL 35294 USA
[2] Univ Alabama Birmingham, Dept Epidemiol, Birmingham, AL 35294 USA
[3] Rush Univ, Dept Urol, Chicago, IL USA
[4] Stanford Univ, Dept Urol, Sch Med, Stanford, CA USA
[5] Yale Sch Med, Dept Urol, New Haven, CT USA
[6] Loyola Univ Med Ctr, Dept Urol, Maywood, IL USA
[7] Univ Miami, Dept Urol, Miller Sch Med, Miami, FL USA
[8] Emory Univ, Dept Urol, Atlanta, GA USA
[9] Emory Healthcare, Winship Canc Inst, Atlanta, GA USA
[10] Loyola Univ Med Ctr, Dept Radiol, Maywood, IL USA
[11] Univ Alabama Birmingham, Dept Radiol, Birmingham, AL USA
[12] Univ Alabama Birmingham, ONeal Comprehens Canc Ctr, Birmingham, AL USA
关键词
active surveillance; cancer screening; multiparametric magnetic resonance imaging; prostatic adenocarcinoma; risk calculator; SYSTEM VERSION 2; BIOPSY;
D O I
10.1002/cncr.34355
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background Most Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions do not contain clinically significant prostate cancer (CSPCa; grade group >= 2). This study was aimed at identifying clinical and magnetic resonance imaging (MRI)-derived risk fac- tors that predict CSPCa in men with PI-RADS 3 lesions. Methods This study analyzed the detection of CSPCa in men who underwent MRI-targeted biopsy for PI-RADS 3 lesions. Multivariable logistic regression models with goodness-of-fit testing were used to identify variables associated with CSPCa. Receiver operating curves and decision curve analyses were used to estimate the clinical utility of a predictive model. Results Of the 1784 men reviewed, 1537 were included in the training cohort, and 247 were included in the validation cohort. The 309 men with CSPCa (17.3%) were older, had a higher prostate-specific antigen (PSA) density, and had a greater likelihood of an anteriorly located lesion than men without CSPCa (p < .01). Multivariable analysis revealed that PSA density (odds ratio [OR], 1.36; 95% confidence interval [CI], 1.05-1.85; p < .01), age (OR, 1.05; 95% CI, 1.02-1.07; p < .01), and a biopsy-naive status (OR, 1.83; 95% CI, 1.38-2.44) were independently associated with CSPCa. A prior negative biopsy was negatively associated (OR, 0.35; 95% CI, 0.24-0.50; p < .01). The application of the model to the validation cohort resulted in an area under the curve of 0.78. A predicted risk threshold of 12% could have prevented 25% of biopsies while detecting almost 95% of CSPCas with a sensitivity of 94% and a specificity of 34%. Conclusions For PI-RADS 3 lesions, an elevated PSA density, older age, and a biopsy-naive status were associated with CSPCa, whereas a prior negative biopsy was negatively associated. A predictive model could prevent PI-RADS 3 biopsies while missing few CSPCas. Lay summary Among men with an equivocal lesion (Prostate Imaging-Reporting and Data System 3) on multiparametric magnetic resonance imaging (mpMRI), those who are older, those who have a higher prostate-specific antigen density, and those who have never had a biopsy before are at higher risk for having clinically significant prostate cancer (CSPCa) on subsequent biopsy. However, men with at least one negative biopsy have a lower risk of CSPCa. A new predictive model can greatly reduce the need to biopsy equivocal lesions noted on mpMRI while missing only a few cases of CSPCa.
引用
收藏
页码:3287 / 3296
页数:10
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