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AB190. Could magnetic resonance imaging help identify the presence of prostate cancer before initial biopsy? The development of nomogram predicting the outcomes of prostate biopsy in the Chinese population

OBJECTIVE: To investigate the effectiveness of magnetic resonance imaging (MRI) in diagnosing prostate cancer (PCa) and high-grade prostate cancer (HGPCa) before transrectal ultrasound (TRUS)-guided biopsy. METHODS: The clinical data of 894 patients who received TRUS-guided biopsy and prior MRI test...

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Detalles Bibliográficos
Autores principales: Fang, Dong, Ren, Da, Yu, Wei, Li, Xuesong, Yin, Wenshi, Yu, Xiaoteng, Yang, Kunlin, Liu, Pei, Shan, Gangzhi, Li, Shuqing, He, Qun, Xin, Zhongcheng, Zhou, Liqun, Zhao, Chenglin, Wang, Rui, Wang, Xiaoying, Wang, Huihui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4842614/
http://dx.doi.org/10.21037/tau.2016.s190
Descripción
Sumario:OBJECTIVE: To investigate the effectiveness of magnetic resonance imaging (MRI) in diagnosing prostate cancer (PCa) and high-grade prostate cancer (HGPCa) before transrectal ultrasound (TRUS)-guided biopsy. METHODS: The clinical data of 894 patients who received TRUS-guided biopsy and prior MRI test from a large Chinese center was reviewed. All MRIs were re-reviewed and assigned as Grade 0-2 (negative; suspicious; positive) based on Prostate Imaging Reporting and Data System (PI-RADS) scoring. We constructed two models both in predicting PCa and HGPCa: Model 1 with MRI and Model 2 without MRI. Other clinical factors include age, digital rectal examination, PSA, free-PSA, volume and TRUS. RESULTS: PCa and HGPCa were present in 434 (48.5%) and 218 (24.4%) patients each. An MRI Grade 0, 1 and 2 were assigned in 324 (36.2%), 193 (21.6%) and 377 (42.2%) patients, respectively, which was associated with the presence of PCa (P<0.001) and HGPCa (P<0.001). Particularly in patients with age ≤0.001). Particularly in patients with age and 218 (24.4%) patients each. An MRI Grade 0, 1 and 2 were assc-statistic of Model 1 and Model 2 for predicting PCa was 0.875 and 0.841 each (Z=4.2302, P<0.001), while for predicting HGPCa was 0.872 and 0.850 (Z=3.265, P=0.001). Model 1 exhibited higher sensitivity and specificity at same cut-offs and decision curve analysis also suggested the favorable clinical utility of Model 1. CONCLUSIONS: Prostate MRI before biopsy could well predict the presence of PCa and HGPCa, especially in younger patients. The incorporation of MRI in nomograms could increase predictive accuracy.