The Prostate Health Index aids multi-parametric MRI in diagnosing significant prostate cancer

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作者
Yu-Hua Fan
Po-Hsun Pan
Wei-Ming Cheng
Hsin-Kai Wang
Shu-Huei Shen
Hsian-Tzu Liu
Hao-Min Cheng
Wei-Ren Chen
Tzu-Hao Huang
Tzu-Chun Wei
I-Shen Huang
Chih-Chieh Lin
Eric Y. H. Huang
Hsiao-Jen Chung
William J. S. Huang
Tzu-Ping Lin
机构
[1] Taipei Veterans General Hospital,Department of Urology
[2] National Yang-Ming University,Department of Urology, School of Medicine
[3] National Yang-Ming University,Shu
[4] Taipei City Hospital,Tien Urological Institute
[5] Taipei Veterans General Hospital,Division of Urology, Department of Surgery, Zhongxiao Branch
[6] Taipei Veterans General Hospital,Department of Radiology
[7] National Yang-Ming University,Center for Evidence
[8] National Yang-Ming University,Based Medicine
[9] National Yang-Ming University,School of Medicine
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摘要
To evaluate the performance of the Prostate Health Index (PHI) in magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion prostate biopsy for the detection of clinically significant prostate cancer (csPCa). We prospectively enrolled 164 patients with at least one Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) ≥ 3 lesions who underwent MRI-TRUS fusion prostate biopsy. Of the PSA-derived biomarkers, the PHI had the best performance in predicting csPCa (AUC 0.792, CI 0.707–0.877) in patients with PI-RADS 4/5 lesions. Furthermore, the predictive power of PHI was even higher in the patients with PI-RADS 3 lesions (AUC 0.884, CI 0.792–0.976). To minimize missing csPCa, we used a PHI cutoff of 27 and 7.4% of patients with PI-RADS 4/5 lesions could have avoided a biopsy. At this level, 2.0% of cases with csPCa would have been missed, with sensitivity and NPV rates of 98.0% and 87.5%, respectively. However, the subgroup of PI-RADS 3 was too small to define the optimal PHI cutoff. PHI was the best PSA-derived biomarker to predict csPCa in MRI-TRUS fusion prostate biopsies in men with PI-RADS ≥ 3 lesions, especially for the patients with PI-RADS 3 lesions who gained the most value.
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