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The function of Prostate Health Index in detecting clinically significant prostate cancer in the PI-RADS 3 population: a multicenter prospective study

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Abstract

Purpose

The purpose of this study is to identify patients in the prostate imaging reporting and data system (PI-RADS) 3 population who need biopsy by using prostate health index (PHI) and other clinical parameters in order to avoid unnecessary biopsies.

Methods

A total of 302 patients from four hospital were enrolled, and 92 patients with PI-RADS 3 were included finally. All patients were biopsy-naïve and had suspicion of prostate cancer (PCa) with PSA level in 4–20 ng/ml and a normal digital rectal exam. Univariable and stepwise forward multivariable logistic regression analyses were used to evaluated the risk factors. The sensitivity, specificity, and positive and negative predictive values of different cut-off value of PHI were calculated for the diagnosis of clinically significant prostate cancer (CSPCa).

Results

The overall patient’s mean age was 65.65 ± 9.55 years, median PSA was 7.68 (5.28–12.07) ng/ml and median PHI was 43.80 (33.09–64.69). PCa was identified in 32.61% (30/92) of PI-RADS 3 and CSPCa was identified in 28.26% (26/92) of PI-RADS 3. The risk factors for detecting PCa and CSPCa in multivariable regression analysis were age and PHI. When the biopsy was restricted to those PHI ≥ 43.5, 42.39% unnecessary biopsied could avoid. The sensitivity, specificity, positive predictive value and negative predictive value for the detection of CSPCa in the PHI ≥ 43.5 were 92.31%, 63.64%, 50% and 95.45% respectively.

Conclusion

The inclusion of PHI in the diagnosis of the PI-RADS 3 population may avoid many unnecessary biopsies. The multivariable models could increase the detection of cancer.

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Data Availability

The data that supports the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Siegel RL, Miller KD, Fuchs HE, Jemal A (2022) Cancer statistics, 2022. CA Cancer J Clin 72(1):7–33. https://doi.org/10.3322/caac.21708

    Article  PubMed  Google Scholar 

  2. Kasivisvanathan V, Rannikko AS, Borghi M, Panebianco V, Mynderse LA, Vaarala MH, Briganti A, Budaus L, Hellawell G, Hindley RG, Roobol MJ, Eggener S, Ghei M, Villers A, Bladou F, Villeirs GM, Virdi J, Boxler S, Robert G, Singh PB, Venderink W, Hadaschik BA, Ruffion A, Hu JC, Margolis D, Crouzet S, Klotz L, Taneja SS, Pinto P, Gill I, Allen C, Giganti F, Freeman A, Morris S, Punwani S, Williams NR, Brew-Graves C, Deeks J, Takwoingi Y, Emberton M, Moore CM, Collaborators PSG (2018) MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med 378(19):1767–1777. https://doi.org/10.1056/NEJMoa1801993

    Article  PubMed  PubMed Central  Google Scholar 

  3. Mottet N, van den Bergh RCN, Briers E, Van den Broeck T, Cumberbatch MG, De Santis M, Fanti S, Fossati N, Gandaglia G, Gillessen S, Grivas N, Grummet J, Henry AM, van der Kwast TH, Lam TB, Lardas M, Liew M, Mason MD, Moris L, Oprea-Lager DE, van der Poel HG, Rouviere O, Schoots IG, Tilki D, Wiegel T, Willemse PM, Cornford P (2021) EAU-EANM-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer-2020 Update. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent. Eur Urol 79(2):243–262. https://doi.org/10.1016/j.eururo.2020.09.042

    Article  CAS  PubMed  Google Scholar 

  4. Moldovan PC, Van den Broeck T, Sylvester R, Marconi L, Bellmunt J, van den Bergh RCN, Bolla M, Briers E, Cumberbatch MG, Fossati N, Gross T, Henry AM, Joniau S, van der Kwast TH, Matveev VB, van der Poel HG, De Santis M, Schoots IG, Wiegel T, Yuan CY, Cornford P, Mottet N, Lam TB, Rouvière O (2017) What is the negative predictive value of multiparametric magnetic resonance imaging in excluding prostate cancer at biopsy? A Systematic Review and Meta-analysis from the European Association of Urology Prostate Cancer Guidelines Panel. Eur Urol 72(2):250–266. https://doi.org/10.1016/j.eururo.2017.02.026

    Article  PubMed  Google Scholar 

  5. Panebianco, V., F. Barchetti, A. Sciarra, A. Ciardi, E.L. Indino, R. Papalia, M. Gallucci, V. Tombolini, V. Gentile, C. Catalano (2015) Multiparametric magnetic resonance imaging vs. standard care in men being evaluated for prostate cancer: a randomized study. Urol Oncol 33(1): p. 17.e1–17.e7. DOI: https://doi.org/10.1016/j.urolonc.2014.09.013.

  6. Barentsz JO, Richenberg J, Clements R, Choyke P, Verma S, Villeirs G, Rouviere O, Logager V, Fütterer JJ (2012) ESUR prostate MR guidelines 2012. Eur Radiol 22(4):746–757. https://doi.org/10.1007/s00330-011-2377-y

    Article  PubMed  PubMed Central  Google Scholar 

  7. Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S (2016) PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol 69(1):16–40. https://doi.org/10.1016/j.eururo.2015.08.052

    Article  PubMed  Google Scholar 

  8. Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, Tempany CM, Choyke PL, Cornud F, Margolis DJ, Thoeny HC, Verma S, Barentsz J, Weinreb JC (2019) Prostate Imaging Reporting and Data System Version 2.1: update of Prostate Imaging Reporting and Data System Version 2. Eur Urol 76(3):340–351. https://doi.org/10.1016/j.eururo.2019.02.033

    Article  PubMed  Google Scholar 

  9. van der Sar ECA, Kasivisvanathan V, Brizmohun M, Freeman A, Punwani S, Hamoudi R, Emberton M (2019) Management of radiologically indeterminate magnetic resonance imaging signals in men at risk of prostate cancer. Eur Urol Focus 5(1):62–68. https://doi.org/10.1016/j.euf.2017.03.016

    Article  PubMed  Google Scholar 

  10. Epstein, J.I., Allsbrook, Jr., W.C., Amin, M.B., Egevad, L.L. (2005) The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. Am J Surg Pathol. 29(9): 1228–42. https://doi.org/10.1097/01.pas.0000173646.99337.b1

  11. Lee CU, Lee SM, Chung JH, Kang M, Sung HH, Jeon HG, Jeong BC, Seo SI, Jeon SS, Lee HM, Song W (2022) Clinical Utility of Prostate Health Index for Diagnosis of Prostate Cancer in Patients with PI-RADS 3 Lesions. Cancers (Basel). https://doi.org/10.3390/cancers14174174

    Article  PubMed  PubMed Central  Google Scholar 

  12. Chiu PK, Ng CF, Semjonow A, Zhu Y, Vincendeau S, Houlgatte A, Lazzeri M, Guazzoni G, Stephan C, Haese A, Bruijne I, Teoh JY, Leung CH, Casale P, Chiang CH, Tan LG, Chiong E, Huang CY, Wu HC, Nieboer D, Ye DW, Bangma CH, Roobol MJ (2019) 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 75(4):558–561. https://doi.org/10.1016/j.eururo.2018.10.047

    Article  PubMed  Google Scholar 

  13. Pantel K, Alix-Panabières C (2013) Real-time liquid biopsy in cancer patients: fact or fiction? Cancer Res 73(21):6384–6388. https://doi.org/10.1158/0008-5472.Can-13-2030

    Article  CAS  PubMed  Google Scholar 

  14. Filianoti A, Costantini M, Bove AM, Anceschi U, Brassetti A, Ferriero M, Mastroianni R, Misuraca L, Tuderti G, Ciliberto G, Simone G (2022) Volatilome Analysis in Prostate Cancer by Electronic Nose: A Pilot Monocentric Study. Cancers (Basel). https://doi.org/10.3390/cancers14122927

    Article  PubMed  Google Scholar 

  15. Rouvière O, Puech P, Renard-Penna R, Claudon M, Roy C, Mège-Lechevallier F, Decaussin-Petrucci M, Dubreuil-Chambardel M, Magaud L, Remontet L, Ruffion A, Colombel M, Crouzet S, Schott AM, Lemaitre L, Rabilloud M, Grenier N (2019) 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 20(1):100–109. https://doi.org/10.1016/s1470-2045(18)30569-2

    Article  PubMed  Google Scholar 

  16. Ferriero M, Tuderti G, Muto GL, Fiori C, Bove AM, Mastroianni R, Anceschi U, Misuraca L, Brassetti A, De Cillis S, Checcucci E, Guaglianone S, Gallucci M, Porpiglia F, Simone G (2022) Diagnostic performance of fusion (US/MRI guided) prostate biopsy: propensity score matched comparison of elastic versus rigid fusion system. World J Urol 40(4):991–996. https://doi.org/10.1007/s00345-021-03921-0

    Article  CAS  PubMed  Google Scholar 

  17. Ferriero, M., U. Anceschi, A.M. Bove, L. Bertini, R.S. Flammia, G. Zeccolini, D.E.C. B, G. Tuderti, R. Mastroianni, L. Misuraca, A. Brassetti, S. Guaglianone, M. Gallucci, A. Celia, and G. Simone,(2021)Fusion US/MRI prostate biopsy using a computer aided diagnostic (CAD) system. Minerva Urol Nephrol. 73(5): p. 616–624DOI: https://doi.org/10.23736/S2724-6051.20.04008-4.

  18. Yaguchi, G., H.J. Tang, M. Deebajah, J. Keeley, M. Pantelic, S. Williamson, N. Gupta, J.O. Peabody, M. Menon, A. Dabaja, and S. Alanee,(2020)The effect of multiplicity of PI-RADS 3 lesions on cancer detection rate of confirmatory targeted biopsy in patients diagnosed with prostate cancer and managed with active surveillance. Urol Oncol. 38(6): p. 599 e9–599 e13DOI: https://doi.org/10.1016/j.urolonc.2020.03.002.

  19. Scialpi M, Martorana E, Aisa MC, Rondoni V, D’Andrea A, Bianchi G (2017) Score 3 prostate lesions: a gray zone for PI-RADS v2. Turk J Urol 43(3):237–240. https://doi.org/10.5152/tud.2017.01058

    Article  PubMed  PubMed Central  Google Scholar 

  20. Rico, L., L. Blas, G. Vitagliano, P. Contreras, H. Rios Pita, and C. Ameri (2021) PI-RADS 3 lesions: Does the association of the lesion volume with the prostate-specific antigen density matter in the diagnosis of clinically significant prostate cancer? Urol Oncol. 39(7): 431 e9–431 e13. DOI: https://doi.org/10.1016/j.urolonc.2020.11.010.

  21. Gortz M, Radtke JP, Hatiboglu G, Schutz V, Tosev G, Guttlein M, Leichsenring J, Stenzinger A, Bonekamp D, Schlemmer HP, Hohenfellner M, Nyarangi-Dix JN (2021) The Value of Prostate-specific Antigen Density for Prostate Imaging-Reporting and Data System 3 Lesions on Multiparametric Magnetic Resonance Imaging: A Strategy to Avoid Unnecessary Prostate Biopsies. Eur Urol Focus 7(2):325–331. https://doi.org/10.1016/j.euf.2019.11.012

    Article  PubMed  Google Scholar 

  22. Gomez Rivas J, Giganti F, Alvarez-Maestro M, Freire MJ, Kasivisvanathan V, Martinez-Pineiro L, Emberton M (2019) Prostate Indeterminate Lesions on Magnetic Resonance Imaging-Biopsy Versus Surveillance: A Literature Review. Eur Urol Focus 5(5):799–806. https://doi.org/10.1016/j.euf.2018.02.012

    Article  PubMed  Google Scholar 

  23. Fenstermaker M, Mendhiratta N, Bjurlin MA, Meng X, Rosenkrantz AB, Huang R, Deng FM, Zhou M, Huang WC, Lepor H, Taneja SS (2017) Risk Stratification by Urinary Prostate Cancer Gene 3 Testing Before Magnetic Resonance Imaging-Ultrasound Fusion-targeted Prostate Biopsy Among Men With No History of Biopsy. Urology 99:174–179. https://doi.org/10.1016/j.urology.2016.08.022

    Article  PubMed  Google Scholar 

  24. Distler FA, Radtke JP, Bonekamp D, Kesch C, Schlemmer HP, Wieczorek K, Kirchner M, Pahernik S, Hohenfellner M, Hadaschik BA (2017) The Value of PSA Density in Combination with PI-RADS™ for the Accuracy of Prostate Cancer Prediction. J Urol 198(3):575–582. https://doi.org/10.1016/j.juro.2017.03.130

    Article  PubMed  Google Scholar 

  25. Niu XK, Li J, Das SK, Xiong Y, Yang CB, Peng T (2017) Developing a nomogram based on multiparametric magnetic resonance imaging for forecasting high-grade prostate cancer to reduce unnecessary biopsies within the prostate-specific antigen gray zone. BMC Med Imaging 17(1):11. https://doi.org/10.1186/s12880-017-0184-x

    Article  PubMed  PubMed Central  Google Scholar 

  26. Hsieh PF, Li WJ, Lin WC, Chang H, Chang CH, Huang CP, Yang CR, Chen WC, Chang YH, Wu HC (2020) Combining prostate health index and multiparametric magnetic resonance imaging in the diagnosis of clinically significant prostate cancer in an Asian population. World J Urol 38(5):1207–1214. https://doi.org/10.1007/s00345-019-02889-2

    Article  PubMed  Google Scholar 

  27. Zhou Y, Qi W, Cui J, Zhong M, Lv G, Qu S, Chen S, Li R, Shi B, Zhu Y (2022) Construction and Comparison of Different Models in Detecting Prostate Cancer and Clinically Significant Prostate Cancer. Front Oncol 12:911725. https://doi.org/10.3389/fonc.2022.911725

    Article  PubMed  PubMed Central  Google Scholar 

  28. Fan YH, Pan PH, Cheng WM, Wang HK, Shen SH, Liu HT, Cheng HM, Chen WR, Huang TH, Wei TC, Huang IS, Lin CC, Huang EYH, Chung HJ, Huang WJS, Lin TP (2021) The Prostate Health Index aids multi-parametric MRI in diagnosing significant prostate cancer. Sci Rep 11(1):1286. https://doi.org/10.1038/s41598-020-78428-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, Collaco-Moraes Y, Ward K, Hindley RG, Freeman A, Kirkham AP, Oldroyd R, Parker C, Emberton M (2017) Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. The Lancet 389(10071):815–822. https://doi.org/10.1016/s0140-6736(16)32401-1

    Article  Google Scholar 

  30. Schoots IG (2018) MRI in early prostate cancer detection: how to manage indeterminate or equivocal PI-RADS 3 lesions? Transl Androl Urol. 7(1):70–82. https://doi.org/10.21037/tau.2017.12.31

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 81970661 and 82170790 to BS) and the Natural Science Foundation of Shandong Province (ZR2021MH318 to YFZ).

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Author notes

  1. Shouzhen Chen and Yaofeng Zhu have contributed equally to this work and should be considered as corresponding authors.

Authors and Affiliations

  1. Department of Urology, Qilu hospital of Shandong University, Jinan, 250012, Shandong, China

    Yongheng Zhou, Wenqiang Qi, Minglei Zhong, Guangda Lv, Zhiwen Jiang, Meikai Zhu, Wenfu Wang, Benkang Shi, Shouzhen Chen & Yaofeng Zhu

  2. Department of Urology, Shandong Provincial Hospital, Jinan, China

    Qiang Fu

  3. Department of Urology, Linyi People’s Hospital, Linyi, China

    Zhiqiang Shao

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  1. Yongheng Zhou
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Contributions

YHZ contributed to project development, data collection, data analysis, and manuscript writing. QF performed data collection and data analysis. ZS performed data collection and manuscript writing. WQ carried out data analysis. MZ performed data collection. GL carried out data analysis. ZJ and MZ provided software. WW performed manuscript writing. BS contributed to project development and funding acquisition. SC contributed to project development and writing—review and editing. YFZ contributed to project development, funding acquisition, and writing—review and editing.

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Correspondence to Shouzhen Chen or Yaofeng Zhu.

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Zhou, Y., Fu, Q., Shao, Z. et al. The function of Prostate Health Index in detecting clinically significant prostate cancer in the PI-RADS 3 population: a multicenter prospective study. World J Urol 41, 455–461 (2023). https://doi.org/10.1007/s00345-022-04272-0

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