|Year : 2023 | Volume
| Issue : 2 | Page : 86-92
Prostate biopsy strategy integrating prostate health index and multiparametric magnetic resonance imaging optimizes the predictive value of clinically significant prostate cancer in prostate imaging reporting and data system gray-zone imaging
Shih-Ting Chiu1, Yu-Ching Chen2, Chao-Yuan Huang1, Yung-Ting Cheng3, Yeong-Shiau Pu1, Yu-Chuan Lu1, Chih-Hung Chiang4, Pei-Ling Chen1, Jeff S Chueh1, Jian-Hua Hong1
1 Department of Urology, National Taiwan University Hospital, Taipei, Taiwan
2 Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
3 Department of Urology, National Taiwan University Hospital, Hsin-Chu Branch, Hsinchu City, Taiwan
4 Department of Urology/Medical Research and Education, Taipei Veterans General Hospital, Yuan-Shan /Su-Ao Branch, Yi-Lan, Taiwan
|Date of Submission||14-Mar-2022|
|Date of Decision||30-Jun-2022|
|Date of Acceptance||02-Aug-2022|
|Date of Web Publication||17-Jun-2023|
No. 7, Zhongshan S. Road, Zhongzheng Dist., Taipei City 100
Source of Support: None, Conflict of Interest: None
Purpose: The Prostate Health Index (PHI) and multiparametric magnetic resonance imaging (mpMRI) are used as complementary tools for more accurate diagnosis in men with suspected prostate cancer (PCa). This study investigated whether the combination of PHI and mpMRI better predict clinically significant PCa (csPCa), defined as a Gleason score of ≥7. Materials and Methods: Ninety-four men with clinical suspicion of csPCa were prospectively included. PHI was determined before the prostate biopsy. A uroradiologist reviewed mpMRI findings by using the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS version 2.1). Fusion-targeted biopsy with systematic biopsy was performed in patients with any suspicious lesions on MRI (PI-RADS assessment category ≥3), whereas systematic biopsy was performed in patients without suspicious lesions. The diagnostic values of different biomarkers and PI-RADS were compared by the area under the receiver operating curve (area under the curve [AUC]) for detecting csPCa. Results: Forty-nine (52%) patients were diagnosed with csPCa. The csPCa group had higher median PHI and more abnormal MRI findings than did the non-csPCa group. The median total prostate-specific antigen (PSA) level was similar between the PI-RADS 3 and 4 lesion groups. The median PHI values increased and more patients were diagnosed as having csPCa with an increase in PI-RADS. The receiver operating characteristic curve indicated that PHI and MRI (AUC 0.85 and 0.82, respectively) predicted csPCa more accurately than did the total PSA, free PSA ratio, and PSA density. Adding PHI to mpMRI significantly increased the diagnostic accuracy for csPCa (P = 0.004). PHI remained the optimal biomarker in patients with “gray zone” PI-RADS 3 or PI-RADS 4 lesions. Conclusion: PHI can guide decision-making for prostate biopsy for patients with gray-zone mpMRI lesions. We proposed a biopsy strategy incorporating PHI and MRI which resulted in the avoidance of biopsies in 35% of the patients.
Keywords: Clinically significant prostate cancer, prostate health index, prostate imaging reporting and data system, prostate magnetic resonance imaging
|How to cite this article:|
Chiu ST, Chen YC, Huang CY, Cheng YT, Pu YS, Lu YC, Chiang CH, Chen PL, Chueh JS, Hong JH. Prostate biopsy strategy integrating prostate health index and multiparametric magnetic resonance imaging optimizes the predictive value of clinically significant prostate cancer in prostate imaging reporting and data system gray-zone imaging. Urol Sci 2023;34:86-92
|How to cite this URL:|
Chiu ST, Chen YC, Huang CY, Cheng YT, Pu YS, Lu YC, Chiang CH, Chen PL, Chueh JS, Hong JH. Prostate biopsy strategy integrating prostate health index and multiparametric magnetic resonance imaging optimizes the predictive value of clinically significant prostate cancer in prostate imaging reporting and data system gray-zone imaging. Urol Sci [serial online] 2023 [cited 2023 Oct 2];34:86-92. Available from: https://www.e-urol-sci.com/text.asp?2023/34/2/86/378891
| Introduction|| |
Prostate cancer (PCa) is the second-most common solid tumor in men and the fifth-leading cause of cancer deaths worldwide, based on data provided in a global database in 2020. Early detection of PCa using the prostate-specific antigen (PSA) test may reduce the risk of metastasis; however, the PSA test might result in overdiagnosis of indolent tumors, causing patient anxiety and biopsy-related complications., For patients requiring biopsy, diagnostic tools, such as novel biomarkers and imaging modalities, may help differentiate clinically significant PCa (csPCa) from heterogeneous PCa, thereby preventing unnecessary biopsies.
The prostate health index (PHI) test, approved by the US Food and Drug Administration in 2012, is indicated for men with nonsuspicious digital rectal examination and a PSA level between 4 and 10 ng/mL. The PHI is calculated using a mathematical formula that combines total PSA (tPSA), free PSA (fPSA), and (−2) proPSA (p2PSA), which is selectively increased in cancer cells. Various studies have reported that the PHI test has high diagnostic accuracy and indicated that higher PHI values are associated with higher csPCa risk.,,, Several large trials have evaluated the utility of multiparametric magnetic resonance imaging (mpMRI) for the prediction of csPCa, with promising results.,, MpMRI, along with the Prostate Imaging Reporting and Data System (PI-RADS), can be used to obtain information on lesion characteristics and location. With the advent of mpMRI, the targeted biopsies of lesions with a PI-RADS assessment category of ≥3 increased the detection rate of csPCa with approaches, including cognitive biopsy, software-assisted fusion biopsy, and in-bore MRI-guided biopsy. (MRI/transrectal ultrasound [TRUS]) fusion-guided biopsy is accurate, cost-effective, and recommended for patients with suspicion of csPCa before the negative systematic biopsy. Current guidelines recommend using either the PHI or mpMRI for patients with suspicion of csPCa before prostate biopsy; however, the diagnostic accuracy of the combination of the two tests has not yet been validated.
The diagnostic accuracy of the PHI test is comparable to that of mpMRI; however, the accuracy for predicting csPCa might be higher if the two tests are combined., Herein, we developed a diagnostic algorithm integrating the PHI test and mpMRI for clinically challenging scenarios and determined the predictive value of various PSA derivatives, PHI values, and mpMRI in groups with different PCa risks.
| Materials and Methods|| |
We prospectively enrolled patients with a clinical suspicion of PCa or those with more aggressive PCa with a prior diagnosis of low-grade PCa from February 2017 to May 2021 from a single tertiary center. The enrollment criteria for prostate biopsy include elevated PSA, abnormal digital rectal examination, or suspicious prostate lesions on MRI images. Patients with low-grade PCa had not received any PCa-related treatment, and a re-biopsy was recommended after a multidisciplinary team evaluation for PI-RADS ≥4 lesions on MRI.
All prostate images were taken 1 year before the biopsy with either a 1.5T or 3T MRI system without an endorectal coil. A single experienced uroradiologist interpreted all prostate MRI images with 11 years of radiological experience and 7 years of urogenital imaging experience. The radiologist had an abundant prostate MRI reading experience with more than 1000 cases/year. Each MRI lesion was graded based on its characteristics on T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced imaging using PI-RADS version 2.1. Patients with documented 5α-reductase inhibitor use, urinary tract infection, or a history of the transurethral resection of the prostate were excluded. Blood samples for the PHI test were collected before the prostate biopsy. A total of 94 patients who provided written informed consent were included in the final analysis. This study was approved by the institutional review board of the National Taiwan University Hospital (Approval Number: 201612091RIPD; Approval Date: January 2017).
The tPSA, fPSA, and p2PSA levels in the blood samples were measured using the Beckman Coulter Access 2 immunoassay analyzer (Beckman Coulter, Taiwan Inc.) before the biopsy. The percent fPSA was calculated as fPSA/tPSA × 100%. The PHI was calculated as (p2PSA/fPSA) × √tPSA. Prostate volume was estimated through MRI using the standard ellipsoid formula: width × height × length × 0.52. The PSA density (PSAD) was calculated as tPSA/prostate volume.
Urologists performed TRUS-guided systematic prostate biopsy of at least 12 cores in patients with normal prostate imaging results. In patients with any abnormal lesion (PI-RADS Assessment Category ≥3), the MR/TRUS fusion biopsy was conducted by a single uroradiologist who performed segmentation, rigid fusion, and subsequent biopsy with the Toshiba Aplio 500 ultrasound SmartFusion system. The patients were placed in the left lateral decubitus position. During the procedure, a peri-prostatic nerve block, rectal lidocaine gel, and intravenous 0.05–0.1 mg fentanyl were applied as local anesthesia. An MR/TRUS-targeted biopsy of at least two cores was performed in each lesion, followed by a 12-core systematic biopsy at the prostate gland.
The primary outcome was csPCa found on biopsy, defined as a Gleason score (GS) of ≥7 based on pathological findings. The median and interquartile range are reported for continuous variables. Significant differences were examined using the Mann–Whitney U-test for continuous variables and the Chi-square test for categorical variables. The receiver operating characteristic curve (ROC) was plotted to evaluate the diagnostic accuracy of different markers, and the area under the curve (AUC) was compared using the DeLong test. Statistical analyses were performed using IBM SPSS Statistics (version 22.0; Armonk, NY, USA: IBM Corp.). A two-sided P < 0.05 was considered statistically significant.
| Results|| |
Among the 94 patients, 49 (52%) were diagnosed with csPCa, nine (9.6%) of whom had a GS of 6. Furthermore, of the 54 (57%) patients who underwent prior prostate biopsy, 44 and 10 were previously diagnosed with benign lesions and low-grade PCa, respectively. Among the 94 patients, 79 (84%) underwent MR/TRUS fusion-guided targeted biopsy, and 24 (26%) had more than one abnormal lesion. Of the 122 lesions, the largest proportion had PI-RADS 4 lesions (49%), followed by those with PI-RADS 3 lesions (18%) and PI-RADS 5 lesions (17%). [Table 1] summarizes the characteristics of the current cohort. Compared with the noncsPCa group, the patients in the csPCa group were older and had smaller prostates, higher tPSA levels, and higher PHI values. Furthermore, a higher proportion of the patients in the csPCa group than in the noncsPCa group had PI-RADS ≥4 lesions. Among those with a prior low-grade cancer diagnosis, eight out of 10 had a GS upgrade of ≥7, one patient had a GS of 6, and the remaining patient had benign prostate tissue in the targeted biopsy. We stratified our cohort by PI-RADS assessment categories [Table 2]. Per patient-level analysis, the PHI value increased with the PI-RADS. The median PHI values were 34.0, 46.0, and 75.1 for PI-RADS 3, 4, and 5 lesions, respectively. In contrast, the tPSA level was comparable between PI-RADS 3 and PI-RADS 4 lesions, and the PSAD was comparable among normal, PI-RADS 3, and PI-RADS 4 lesions.
|Table 1: Clinical characteristics of 94 patients and their biopsy results stratified by cancer significance|
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|Table 2: Biomarkers and lesion characteristics stratified by Prostate Imaging Reporting and Data System assessment categories|
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[Table 2] presents the characteristics and pathology results of target lesions per lesion-level analysis. The results revealed that 71% of the PI-RADS 5 lesions were in the transitional zone, and only 10% were visible on the ultrasound image. Furthermore, 41% of PI-RADS 3 and 23% of PI-RADS 4 lesions were in the transitional zone, and approximately one-third of the lesions were visible on sonography. The proportion of the patients with diagnoses of PCa and csPCa increased with PI-RADS. The proportions of csPCa in PI-RADS 3, 4, and 5 lesions were 5% (1/22), 62% (37/60), and 76% (16/21), respectively. Moreover, approximately 25% of the PCa PI-RADS 5 lesions had a GS of 6.
The ROC curve was plotted to examine the ability of each diagnostic marker to identify PCa and csPCa. The tPSA had the lowest AUC value of 0.61 (95% confidence interval [CI] 0.50–0.73) for PCa and 0.67 (95% CI 0.57–0.78) for csPCa [Figure 1]a and [Figure 1]b. The PHI test and mpMRI exhibited the highest performance, with AUC values of 0.85 (95% CI 0.78–0.93) and 0.87 (95% CI 0.79–0.94) for PCa and values of 0.85 (95% CI 0.78–0.93) and 0.82 (95% CI 0.74–0.91) for csPCa, respectively. For the patients with a gray zone for PI-RADS on MRI (PI-RADS 3 and 4), the PHI was determined to be the most favorable biomarker, with an AUC value of 0.79 (95% CI 0.68–0.90) for PCa and 0.78 (95% CI 0.67–0.89) for csPCa [Figure 1]c and [Figure 1]d. Compared with MRI alone, the combination of the PHI test and MRI exhibited significantly better performance for detecting overall PCa (AUC 0.92, 95% CI 0.86–0.97, P = 0.02) and csPCa (AUC 0.89, 95% CI 0.82–0.96, P = 0.004; [Figure 2]a and [Figure 2]b).
|Figure 1: ROC curve analysis of different biomarkers and PI-RADS for (a) any cancer and (b) clinically significant cancers in the overall group. ROC curve analysis of the performance of biomarkers in the prediction of (c) any cancer and (d) clinically significant cancer in the PI-RADS category 3 and 4 subgroups. ROC: Receiver operating characteristic curve, PI-RADS: Prostate imaging reporting and data system|
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|Figure 2: AUC comparison of the performance of the PHI in combination with mpMRI and mpMRI alone in identifying (a) any cancer and (b) clinically significant PCa. AUC: Area under the curve, PHI: Prostate health index, mpMRI: Multiparametric magnetic resonance imaging, PCa: Prostate cancer|
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| Discussion|| |
Our study results indicate that among all biomarkers tested, PHI and MRI are excellent predictors of csPCa (PHI: AUC 0.85, 95% CI 0.78–0.93; MRI: AUC 0.82, 95% CI 0.74–0.91). All patients with PI-RADS 5 lesions were diagnosed with PCa, and 76% of them were diagnosed with csPCa. Furthermore, csPCa was not diagnosed in the patients with no suspicion of PCa on MRI in the final biopsy pathology. In the subgroup analysis of the gray zone in the MRI of PI-RADS 3 and 4 lesions, the diagnostic accuracy of the PHI for csPCa remained the highest (AUC 0.78, 95% CI 0.66–0.90). In addition, we observed a significant improvement in the AUC for csPCa detection when the PHI was combined with mpMRI (AUC 0.89, 95% CI 0.82–0.96, P = 0.004).
A biopsy algorithm was proposed based on our results and those of previous studies in an effort to reduce the need for prostate biopsy [Figure 2]. The evidence for patients who did not undergo MRI before biopsy was based on a large multicenter study that included both European and Asian populations. Asian men were first stratified based on their PSA levels, followed by a corresponding PHI cutoff range for csPCa detection. In biopsy-naïve Asian men (n = 1149) with a PSA level of 2–10 ng/dL, a systematic biopsy is recommended if the PHI cutoff is ≥30, with 90% sensitivity for csPCa diagnosis. A PHI cutoff of ≥35 yields 83.7% sensitivity for csPCa diagnosis in Asian men (n = 439) with a PSA level of 10–20 ng/mL regardless of any negative biopsy history. For patients undergoing MRI before biopsy, biopsy was performed in all patients with PI-RADS 5 lesions but not in those with no suspicion of PCa on MRI (lesions with a PI-RADS assessment category ≤2). The PHI test was performed to determine whether further biopsy was required in patients with PI-RADS 3 and 4 lesions. Biopsy was recommended if the PHI was ≥30 in the biopsy-naïve men and ≥35 in the men with prior negative prostate biopsy. The current strategy exhibited high specificity of 62.2% and sensitivity of 89.8%, preventing the need for biopsy in 35% of the patients compared with other PSA derivatives that missed csPCa in 10.2% of the patients [Table 3]. Half of the patients with low-grade PCa (GS of 6) did not require biopsy with the application of this algorithm.
|Table 3: Specificity, unnecessary biopsy reduction, and missing cases at commonly used cutoff values|
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MpMRI has been reported to prevent unnecessary prostate biopsy in biopsy-naïve men, with a 27% avoidance rate in the PROMIS trial, 28% in the PRECISION trial, and up to 49% in a large prospective and multicenter study.,, However, a negative mpMRI finding might fail to identify approximately 9% of csPCa lesions. Thus, the optimization of mpMRI and other biomarkers to aid clinical decisions remains a goal for clinical physicians. PSAD is the most studied biomarker in combination with MRI. Boesen et al. proposed a strategy of restricting biopsy to only men with highly suspicious MRI findings (Likert scores of ≥4) or a PSAD of ≥0.15 ng/mL/cm3, reducing the biopsy rate to 41%. A retrospective study that included 190 French men reported that the negative predictive value (NPV) of negative mpMRI alone was 94.8% for csPCa, and it increased to 95.8% and 100% when combined with a PSAD of ≤0.15 and ≤0.10 ng/mL/cm3, respectively. Similarly, Zhang et al. demonstrated that the NPV of negative mpMRI for csPCa detection improved with decreasing PSAD, and a nomogram was further established with age, PSAD, and PI-RADS to predict the risk of csPCa.
Gnanapragasam et al. were the first to report the combination of PHI and MRI as a biopsy strategy. They suggested that biopsy should be performed in men with positive MRI showing lesions with a Likert score of ≥3 in PI-RADS version 1 or a PHI value of ≥35 in the presence of nonsuspicious MRI lesions. This strategy detected 99% of csPCa lesions with an NPV of 0.97, preventing biopsy in 45% of patients. Furthermore, compared with mpMRI alone, the combination of the PHI and mpMRI more accurately predicted csPCa (AUC 0.75 vs. 0.64). However, that study excluded independent image reviewers, did not incorporate the most recent PI-RADS version 2.1, and categorized all abnormal lesions (PI-RADS assessment category ≥3) into a single “positive MRI” group. Therefore, with evolving experience in mpMRI interpretation and global standardization, we explored the additional value of combining the PHI and mpMRI in different PI-RADS groups. Our study separated PI-RADS 3 and 4 lesions from PI-RADS 5 lesions because of their different csPCa risks.
Hsieh et al. conducted a prospective study in Taiwan, which included 102 patients with suspicion of PCa who underwent systematic biopsy and cognitive targeted biopsy. Biopsy was performed if patients had PI-RADS 5 lesions on prebiopsy MRI or PI-RADS 3 or 4 lesions with a PHI value of ≥30. Through this strategy, biopsy was prevented in 50% of the patients. Similar to our study, all patients with csPCa had lesions with a PI-RADS assessment category ≥3. Here, we implemented the proposal of Hsieh et al. to separate PI-RADS 5 lesions from others. However, the use of cognitive fusion biopsy without software fusion biopsy may have resulted in lower PCa or csPCa detection rates than those in the current study (PCa/csPCa ratio: 38.2%/23.5% reported by Hsieh et al. vs. 61.8%/52.1% in our study). In their study conducted in Taiwan, Fan et al. included 164 patients with abnormal MRI lesions (PI-RADS ≥3) and performed a 12-core systematic and cognitive MR/TRUS fusion targeted biopsy. The PHI exhibited the most satisfactory performance in predicting csPCa among different PSA derivatives in the subgroups of PI-RADS 4 or 5 lesions (AUC 0.79, 95% CI 0.71–0.88) and PI-RADS 3 lesions (AUC 0.88, 95% CI 0.79–0.98). The cutoff determined using Youden's index was ≥50.1 in the PI-RADS 3 lesion group and ≥48.1 in the PI-RADS 4 or 5 lesion group, which prevented biopsy in 69.1% and 27.5% of patients, respectively. However, using such a high PHI cutoff value for reference may have resulted in many missed cases (5.9% in the PI-RADS 3 lesion group and 27.5% in the PI-RADS 4 or 5 lesion group). In addition, both the studies included patients with prior negative biopsy, which is considered a different risk of PCa; however, none of them included such information in the biopsy strategy as we did in our study.
Sedláčková et al. developed a diagnostic algorithm in a tertiary university hospital incorporating the PHI and mpMRI, starting with a PHI level of ≥40 as a triage, followed by 3T mpMRI as the second step before performing systematic and MR-TRUS biopsy; however, they did not assess diagnostic accuracy. We proposed a biopsy algorithm [Figure 3] based on the results of our study and those of previous multicenter studies. Our algorithm, which incorporated an individual's biopsy history, PHI, and MRI findings, exhibited the highest specificity of 62.2% and sensitivity of 90% among all PSA-related markers for csPCa detection. Our strategy prevented the need for biopsy in 35% of patients and reduced 55% of the diagnosis of clinically insignificant (GS 6) PCa.
|Figure 3: Algorithm of the prostate biopsy strategy incorporating biopsy history, PI-RADS, and PHI. PI-RADS: Prostate imaging reporting and data system, PHI: Prostate health index, PCa: Prostate cancer, csPCa: Clinically significant PCa, PSA: Prostate-specific antigen, MRI: Magnetic resonance imaging|
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The strength of the current prospective study is that an experienced radiologist independently reviewed and interpreted all MRI images. In addition, rather than TRUS or cognitive fusion biopsy, all patients underwent MR/US fusion-guided biopsy using software, resulting in higher accuracy in the final biopsy pathology of the targeted lesion. Finally, this study evidenced the additional value of combining the PHI and mpMRI, as well as a practical algorithm that can be used in clinical practice. However, this study has some limitations. The small sample size limited additional subgroup analyses, such as those of the gray-zone-only MRI patients or biopsy-naïve subgroups.
Furthermore, the current cohort was heterogeneous without the limitation of biopsy history, and the men who received a diagnosis of low-grade PCa before fusion biopsy were included. MR/TRUS fusion biopsy is commonly recommended to patients after a negative or unsatisfactory standard TRUS biopsy. In addition, we included only patients who did not receive any PCa-related treatment before MR/TRUS fusion biopsy if low-grade PCa was diagnosed; thus, the measurements of the serum-level PSA derivatives were not affected. Taken together, we believe that the inclusion criterion of our study enhances the generalizability of our results and is consistent with current clinical practice. The effect of heterogeneity should be minimal because our endpoint was cancer detection rather than clinical oncological outcomes, such as survival. This can be supported by the finding that after the inclusion of individual biopsy history in our proposed biopsy algorithm, the biopsy strategy still exhibited high sensitivity and specificity for csPCa prediction.
| Conclusion|| |
The PHI can guide the biopsy strategy for patients with PI-RADS 3 and 4 lesions and significantly increase the diagnostic accuracy for csPCa. We proposed a biopsy protocol integrating the PHI and PI-RADS, which resulted in high sensitivity and specificity for csPCa detection. Thus, our biopsy strategy can help prevent unnecessary biopsies in approximately 35% of patients.
Data availability statement
All data generated or analyzed during this study are included in this published article.
We thank Chao-Yuan Huang, Chung-Hsin Chen, Jian-Hua Hong, Yeong-Shiau Pu, Shih-Ping Liu, Yu-Chuan Lu, Yi-Kai Chang, Hong-Chiang Chang, Kuo-How Huang, Yuan-Ju Lee, Po-Ming Chow, I-Ni Chiang, Shih-Chun Hung, and Shuo-Meng Wang for providing clinical data for analyses. We thank the research assistants I-Ting Teng and Pei-Yu Hsu for blood specimen collection and analysis. This manuscript was edited by Wallace Academic Editing.
Financial support and sponsorship
Conflicts of interest
Beckman Coulter provided the PHI testing kit; however, the blood sampling, data analyses, and writing were performed by the present researchers. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Prof. Chao-Yuan Huang, Prof. Yeong-Shiau Pu and Prof. Jeff S. Chueh, editorial board members at Urological Science, had no roles in the peer review process of or decision to publish this article. The other authors declared no conflicts of interest in writing this paper.
| References|| |
Gandaglia G, Leni R, Bray F, Fleshner N, Freedland SJ, Kibel A, et al.
Epidemiology and prevention of prostate cancer. Eur Urol Oncol 2021;4:877-92.
Loeb S, Vellekoop A, Ahmed HU, Catto J, Emberton M, Nam R, et al.
Systematic review of complications of prostate biopsy. Eur Urol 2013;64:876-92.
Loeb S, Bjurlin MA, Nicholson J, Tammela TL, Penson DF, Carter HB, et al.
Overdiagnosis and overtreatment of prostate cancer. Eur Urol 2014;65:1046-55.
Ferro M, De Cobelli O, Lucarelli G, Porreca A, Busetto GM, Cantiello F, et al.
Beyond PSA: The role of prostate health index (phi). Int J Mol Sci 2020;21:E1184.
Loeb S, Sanda MG, Broyles DL, Shin SS, Bangma CH, Wei JT, et al.
The prostate health index selectively identifies clinically significant prostate cancer. J Urol 2015;193:1163-9.
Chiu PK, Ng CF, Semjonow A, Zhu Y, Vincendeau S, Houlgatte A, et al.
A multicentre evaluation of the role of the prostate health index (PHI) in regions with differing prevalence of prostate cancer: Adjustment of PHI reference ranges is needed for European and Asian settings. Eur Urol 2019;75:558-61.
Cheng YT, Chiang CH, Pu YS, Liu SP, Lu YC, Chang YK, et al.
The application of p2PSA% and prostate health index in prostate cancer detection: A prospective cohort in a Tertiary Medical Center. J Formos Med Assoc 2019;118:260-7.
Catalona WJ, Partin AW, Sanda MG, Wei JT, Klee GG, Bangma CH, et al.
A multicenter study of [-2]pro-prostate specific antigen combined with prostate specific antigen and free prostate specific antigen for prostate cancer detection in the 2.0 to 10.0 ng/ml prostate specific antigen range. J Urol 2011;185:1650-5.
Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, et al.
Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): A paired validating confirmatory study. Lancet 2017;389:815-22.
Rouvière O, Puech P, Renard-Penna R, Claudon M, Roy C, Mège-Lechevallier F, et al.
Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy-naive patients (MRI-FIRST): A prospective, multicentre, paired diagnostic study. Lancet Oncol 2019;20:100-9.
Kasivisvanathan V, Rannikko AS, Borghi M, Panebianco V, Mynderse LA, Vaarala MH, et al.
MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med 2018;378:1767-77.
Das CJ, Razik A, Sharma S, Verma S. Prostate biopsy: When and how to perform. Clin Radiol 2019;74:853-64.
Benelli A, Vaccaro C, Guzzo S, Nedbal C, Varca V, Gregori A. The role of MRI/TRUS fusion biopsy in the diagnosis of clinically significant prostate cancer. Ther Adv Urol 2020;12. doi:10.1177/1756287220916613.
Carroll PH, Mohler JL. NCCN guidelines updates: Prostate cancer and prostate cancer early detection. J Natl Compr Canc Netw 2018;16:620-3.
Stejskal J, Adamcová V, Záleský M, Novák V, Čapoun O, Fiala V, et al
. The predictive value of the prostate health index vs. multiparametric magnetic resonance imaging for prostate cancer diagnosis in prostate biopsy. World J Urol 2021;39:1889-95.
Druskin SC, Tosoian JJ, Young A, Collica S, Srivastava A, Ghabili K, et al.
Combining Prostate Health Index density, magnetic resonance imaging and prior negative biopsy status to improve the detection of clinically significant prostate cancer. BJU Int 2018;121:619-26.
Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, et al.
Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. Eur Urol 2019;76:340-51.
van der Leest M, Cornel E, Israël B, Hendriks R, Padhani AR, Hoogenboom M, et al.
Head-to-head comparison of transrectal ultrasound-guided prostate biopsy versus multiparametric prostate resonance imaging with subsequent magnetic resonance-guided biopsy in biopsy-naïve men with elevated prostate-specific antigen: A large prospective multicenter clinical study. Eur Urol 2019;75:570-8.
Drost FH, Osses D, Nieboer D, Bangma CH, Steyerberg EW, Roobol MJ, et al.
Prostate magnetic resonance imaging, with or without magnetic resonance imaging-targeted biopsy, and systematic biopsy for detecting prostate cancer: A cochrane systematic review and meta-analysis. Eur Urol 2020;77:78-94.
Boesen L, Nørgaard N, Løgager V, Balslev I, Bisbjerg R, Thestrup KC, et al
. Prebiopsy biparametric magnetic resonance imaging combined with prostate-specific antigen density in detecting and ruling out gleason 7-10 prostate cancer in Biopsy-naïve Men. Eur Urol Oncol 2019;2:311-9.
Anastay V, Gondran-Tellier B, McManus R, Delonca R, Akiki A, Gaillet S, et al.
Nonsuspicious prebiopsy multiparametric MRI: Is prostate biopsy still necessary? Abdom Radiol (NY) 2020;45:4160-5.
Zhang Y, Zeng N, Zhang F, Huang Y, Tian Y. How to make clinical decisions to avoid unnecessary prostate screening in biopsy-naïve men with PI-RADs v2 score ≤3? Int J Clin Oncol 2020;25:175-86.
Gnanapragasam VJ, Burling K, George A, Stearn S, Warren A, Barrett T, et al.
The Prostate Health Index adds predictive value to multi-parametric MRI in detecting significant prostate cancers in a repeat biopsy population. Sci Rep 2016;6:35364.
Hsieh PF, Li WJ, Lin WC, Chang H, Chang CH, Huang CP, et al
. Combining prostate health index and multiparametric magnetic resonance imaging in the diagnosis of clinically significant prostate cancer in an Asian population. World J Urol 2020;38:1207-14.
Fan YH, Pan PH, Cheng WM, Wang HK, Shen SH, Liu HT, et al.
The Prostate Health Index aids multi-parametric MRI in diagnosing significant prostate cancer. Sci Rep 2021;11:1286.
Djavan B, Ravery V, Zlotta A, Dobronski P, Dobrovits M, Fakhari M, et al.
Prospective evaluation of prostate cancer detected on biopsies 1, 2, 3 and 4: When should we stop? J Urol 2001;166:1679-83.
Sedláčková H, Dolejšová O, Hora M, Ferda J, Hes O, Topolčan O, et al.
Prostate cancer diagnostic algorithm as a “road map” from the first stratification of the patient to the final treatment decision. Life (Basel) 2021;11:324.
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]