Advertisement

Natural History of Patients with Prostate MRI Likert 1-3 and Development of RosCaP: a Multivariate Risk Score for Clinically Significant Cancer

  • Luca Orecchia
    Correspondence
    Address for correspondence: Luca Orecchia, Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Rd, Cambridge, CB2 0QQ, UK.
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom

    Urology Unit, Fondazione PTV Policlinico Tor Vergata University Hospital, Rome, Italy
    Search for articles by this author
  • Alessandra Nardi
    Affiliations
    Department of Mathematics, University of Rome Tor Vergata, Italy
    Search for articles by this author
  • Peter Fletcher
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
    Search for articles by this author
  • Simona Ippoliti
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom

    International Medical School, University of Rome Tor Vergata, Italy
    Search for articles by this author
  • Jonathan Grounds
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
    Search for articles by this author
  • Ibifuro Dokubo
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
    Search for articles by this author
  • Claudia Fede Spicchiale
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom

    Urology Unit, Fondazione PTV Policlinico Tor Vergata University Hospital, Rome, Italy
    Search for articles by this author
  • Saiful Miah
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
    Search for articles by this author
  • Roberto Miano
    Affiliations
    Urology Unit, Fondazione PTV Policlinico Tor Vergata University Hospital, Rome, Italy

    Department of Surgical Sciences, University of Rome Tor Vergata, Italy
    Search for articles by this author
  • Author Footnotes
    ⁎ These authors contributed equally to this work
    Tristan Barrett
    Footnotes
    ⁎ These authors contributed equally to this work
    Affiliations
    Radiology Service, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
    Search for articles by this author
  • Author Footnotes
    ⁎ These authors contributed equally to this work
    Christof Kastner
    Footnotes
    ⁎ These authors contributed equally to this work
    Affiliations
    Department of Urology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
    Search for articles by this author
  • Author Footnotes
    ⁎ These authors contributed equally to this work

      Highlights

      • Patients with negative MRI can be safely followed-up without a prostate biopsy.
      • PSA Density levels should guide prostate cancer screening in the community.
      • Age, PSA Density and Likert score are associated with the risk of significant cancer.
      • The RosCaP score may support decision to biopsy in low to equivocal risk cases.

      Abstract

      Introduction

      Clinically significant prostate cancer (csCaP) with Gleason ≥3 + 4 is found in 10% negative prebiopsy multiparametric (mp) MRI cases and varies widely for equivocal mpMRI cases. The objective of this study was to investigate long-term outcomes of patients with negative and equivocal mpMRIs and to develop a predictive score for csCaP risk stratification in this group.

      Patients and Methods

      Patients who underwent an upfront mpMRI between May 2015 and March 2018 with an MRI score Likert 1 to 3 were included in the study. Patients had either a CaP diagnosis at MRI-targeted biopsy or were not diagnosed and attended follow-up in the community. Outcomes were analysed through the Kaplan-Meier estimator and Cox Model. Regression coefficients of significant variables were used to develop a Risk of significant Cancer of the Prostate score (RosCaP).

      Results

      At first assessment 281/469 patients had mpMRI only and 188/469 mpMRI and biopsy, 26 csCaP were found at biopsy, including 10/26 in Likert 3 patients. 12/371 patients discharged without CaP after first assessment were diagnosed with csCaP during a median of 34.2 months’ follow-up, 11/12 diagnosis occurred in patients omitting initial biopsy. csCaP diagnosis-free survival was 95.7% in the MRI group and 99.1% in the biopsy group. From these outcomes, a continuous RosCaP score was developed: RosCaP = 0.083 x Age - 0.202 x (1/PSA Density) + 0.786 (if Likert 3), and 4 risk classes were proposed. Limitations include retrospective design and absence of external validation.

      Conclusion

      Age, PSA Density and MRI Likert score were significantly associated to the risk of csCaP and utilised to devise the novel RosCap predictive score focused to support risk assessment in patients with negative or equivocal mpMRI results.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Clinical Genitourinary Cancer
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Sathianathen NJ
        • Omer A
        • Harriss E
        • et al.
        Negative predictive value of multiparametric Magnetic Resonance Imaging in the detection of clinically significant Prostate Cancer in the Prostate Imaging reporting and data system era: a systematic review and meta-analysis.
        Eur Urol. 2020; 78: 402-414https://doi.org/10.1016/j.eururo.2020.03.048
        • Drost FJH
        • Osses D
        • Nieboer D
        • 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: 78-94https://doi.org/10.1016/j.eururo.2019.06.023
      1. Mottet N, Cornford P, Van Den Bergh RC, et al. EAU-EANM-ESTRO-ESUR-ISUP-SIOG guidelines on prostate cancer. Edn. presented at the EAU Annual Congress Amsterdam 2022.

      2. NICE guideline [NG131] - prostate cancer: diagnosis and management. Published online May 9, 2019. https://www.nice.org.uk/guidance/ng131 [Last accessed on 13th February 2022]

        • Turkbey B
        • Rosenkrantz AB
        • Haider MA
        • 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: 340-351https://doi.org/10.1016/j.eururo.2019.02.033
        • Barrett T
        • Rajesh A
        • Rosenkrantz AB
        • Choyke PL
        • Turkbey B.
        PI-RADS version 2.1: one small step for prostate MRI.
        Clin Radiol. 2019; 74: 841-852https://doi.org/10.1016/j.crad.2019.05.019
        • Maggi M
        • Panebianco V
        • Mosca A
        • et al.
        Prostate Imaging Reporting and Data System 3 Category cases at Multiparametric Magnetic Resonance for Prostate Cancer: a systematic review and meta-analysis.
        Eur Urol Focus. 2020; 6: 463-478https://doi.org/10.1016/j.euf.2019.06.014
        • Hansen NL
        • Koo BC
        • Warren AY
        • Kastner C
        • Barrett T.
        Sub-differentiating equivocal PI-RADS-3 lesions in multiparametric magnetic resonance imaging of the prostate to improve cancer detection.
        Eur J Radiol. 2017; 95: 307-313https://doi.org/10.1016/j.ejrad.2017.08.017
        • Wadera A
        • Alabousi M
        • Pozdnyakov A
        • et al.
        Impact of PI-RADS Category 3 lesions on the diagnostic accuracy of MRI for detecting prostate cancer and the prevalence of prostate cancer within each PI-RADS category: a systematic review and meta-analysis.
        BJR. 2021; 9420191050https://doi.org/10.1259/bjr.20191050
        • Schoots IG
        • Roobol MJ.
        Multivariate risk prediction tools including MRI for individualized biopsy decision in prostate cancer diagnosis: current status and future directions.
        World J Urol. 2020; 38: 517-529https://doi.org/10.1007/s00345-019-02707-9
        • Alberts AR
        • Roobol MJ
        • Verbeek JFM
        • et al.
        Prediction of high-grade prostate cancer following multiparametric Magnetic Resonance Imaging: improving the rotterdam European randomized study of screening for prostate cancer risk calculators.
        Eur Urol. 2019; 75: 310-318https://doi.org/10.1016/j.eururo.2018.07.031
        • Radtke JP
        • Wiesenfarth M
        • Kesch C
        • et al.
        Combined clinical parameters and multiparametric Magnetic Resonance Imaging for advanced risk modeling of prostate cancer—patient-tailored risk stratification can reduce unnecessary biopsies.
        Eur Urol. 2017; 72: 888-896https://doi.org/10.1016/j.eururo.2017.03.039
        • van Leeuwen PJ
        • Hayen A
        • Thompson JE
        • et al.
        A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy.
        BJU Int. 2017; 120: 774-781https://doi.org/10.1111/bju.13814
        • Mehralivand S
        • Shih JH
        • Rais-Bahrami S
        • et al.
        A Magnetic Resonance Imaging–based prediction model for prostate biopsy risk stratification.
        JAMA Oncol. 2018; 4: 678https://doi.org/10.1001/jamaoncol.2017.5667
        • Saba K
        • Wettstein MS
        • Lieger L
        • et al.
        External validation and comparison of Prostate Cancer risk calculators incorporating multiparametric Magnetic Resonance Imaging for prediction of clinically significant Prostate Cancer.
        J Urol. 2020; 203: 719-726https://doi.org/10.1097/JU.0000000000000622
        • Petersmann AL
        • Remmers S
        • Klein T
        • et al.
        External validation of two MRI-based risk calculators in prostate cancer diagnosis.
        World J Urol. 2021; 39: 4109-4116https://doi.org/10.1007/s00345-021-03770-x
        • Hansen NL
        • Barrett T
        • Koo B
        • et al.
        The influence of prostate-specific antigen density on positive and negative predictive values of multiparametric magnetic resonance imaging to detect Gleason score 7-10 prostate cancer in a repeat biopsy setting.
        BJU Int. 2017; 119: 724-730https://doi.org/10.1111/bju.13619
        • Brizmohun Appayya M
        • Adshead J
        • Ahmed HU
        • et al.
        National implementation of multi-parametric magnetic resonance imaging for prostate cancer detection - recommendations from a UK consensus meeting.
        BJU Int. 2018; 122: 13-25https://doi.org/10.1111/bju.14361
        • Deniffel D
        • Healy GM
        • Dong X
        • et al.
        Avoiding unnecessary Biopsy: MRI-based risk models versus a PI-RADS and PSA density strategy for clinically significant prostate cancer.
        Radiology. 2021; 300: 369-379https://doi.org/10.1148/radiol.2021204112
        • Barrett T
        • Slough R
        • Sushentsev N
        • et al.
        Three-year experience of a dedicated prostate mpMRI pre-biopsy programme and effect on timed cancer diagnostic pathways.
        Clin Radiol. 2019; 74 (894.e1-894.e9)https://doi.org/10.1016/j.crad.2019.06.004
        • Karanasios E
        • Caglic I
        • Zawaideh JP
        • Barrett T.
        Prostate MRI quality: clinical impact of the PI-QUAL score in prostate cancer diagnostic work-up.
        BJR. 2022; (Published online February 18)20211372https://doi.org/10.1259/bjr.20211372
        • Barrett T
        • Padhani AR
        • Patel A
        • et al.
        Certification in reporting multiparametric magnetic resonance imaging of the prostate: recommendations of a UK consensus meeting.
        BJU Int. 2021; 127: 304-306https://doi.org/10.1111/bju.15285
        • de Rooij M
        • Israël B
        • Tummers M
        • et al.
        ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists’ training.
        Eur Radiol. 2020; 30: 5404-5416https://doi.org/10.1007/s00330-020-06929-z
        • Harada T
        • Abe T
        • Kato F
        • et al.
        Five-point Likert scaling on MRI predicts clinically significant prostate carcinoma.
        BMC Urol. 2015; 15: 91https://doi.org/10.1186/s12894-015-0087-5
        • Zawaideh JP
        • Sala E
        • Pantelidou M
        • et al.
        Comparison of Likert and PI-RADS version 2 MRI scoring systems for the detection of clinically significant prostate cancer.
        BJR. 2020; 9320200298https://doi.org/10.1259/bjr.20200298
        • Latifoltojar A
        • Appayya MB
        • Barrett T
        • Punwani S.
        Similarities and differences between Likert and PIRADS v2.1 scores of prostate multiparametric MRI: a pictorial review of histology-validated cases.
        Clin Radiol. 2019; 74 (895.e1-895.e15)https://doi.org/10.1016/j.crad.2019.08.020
        • Ippoliti S
        • Fletcher P
        • Orecchia L
        • Miano R
        • Kastner C
        • Barrett T.
        Optimal biopsy approach for detection of clinically significant prostate cancer.
        BJR. 2022; 9520210413https://doi.org/10.1259/bjr.20210413
        • Epstein JI
        • Allsbrook WC
        • Amin MB
        • Egevad LL.
        The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma.
        Am J Surg Pathol. 2005; 29: 1228-1242https://doi.org/10.1097/01.pas.0000173646.99337.b1
        • Panebianco V
        • Barchetti G
        • Simone G
        • et al.
        Negative Multiparametric Magnetic Resonance Imaging for Prostate Cancer: What's Next?.
        Eur Urol. 2018; 74: 48-54https://doi.org/10.1016/j.eururo.2018.03.007
        • Venderink W
        • van Luijtelaar A
        • van der Leest M
        • et al.
        Multiparametric magnetic resonance imaging and follow-up to avoid prostate biopsy in 4259 men: mpMRI and follow up to avoid prostate biopsy.
        BJU Int. 2019; 124: 775-784https://doi.org/10.1111/bju.14853
        • Barrett T
        • Rajesh A.
        Special issue on prostate imaging.
        Clin Radiol. 2019; 74: 821-822https://doi.org/10.1016/j.crad.2019.06.013
        • Khoo CC
        • Eldred-Evans D
        • Peters M
        • et al.
        Likert vs PI-RADS v2: a comparison of two radiological scoring systems for detection of clinically significant prostate cancer.
        BJU Int. 2020; 125: 49-55https://doi.org/10.1111/bju.14916
        • Lophatananon A
        • Light A
        • Burns-Cox N
        • et al.
        Re-evaluating the diagnostic efficacy of PSA as a referral test to detect clinically significant prostate cancer in contemporary MRI-based image-guided biopsy pathways.
        J Clin Urol. 2021; (Published online December 1205141582110590)https://doi.org/10.1177/20514158211059057
        • Light A
        • Burns-Cox N
        • Maccormick A
        • John J
        • McGrath J
        • Gnanapragasam VJ.
        The diagnostic impact of UK regional variations in age-specific prostate-specific antigen guidelines.
        BJU Int. 2021; 128: 298-300https://doi.org/10.1111/bju.15484
        • Godtman RA
        • Kollberg KS
        • Pihl CG
        • Månsson M
        • Hugosson J.
        The association between age, prostate cancer risk, and higher gleason score in a long-term screening program: results from the Göteborg-1 prostate cancer screening trial.
        Eur Urol. February 2022; (Published onlineS0302283822000197)https://doi.org/10.1016/j.eururo.2022.01.018
        • Huynh-Le M
        • Myklebust TÅ
        • Feng CH
        • et al.
        Age dependence of modern clinical risk groups for localized prostate cancer—a population-based study.
        Cancer. 2020; 126: 1691-1699https://doi.org/10.1002/cncr.32702
        • Falagario UG
        • Jambor I
        • Lantz A
        • et al.
        Combined use of prostate-specific antigen density and Magnetic Resonance Imaging for prostate biopsy decision planning: a retrospective multi-institutional study using the Prostate Magnetic Resonance Imaging Outcome Database (PROMOD).
        Eur Urol Oncol. 2021; 4: 971-979https://doi.org/10.1016/j.euo.2020.08.014
        • Boesen L
        • Nørgaard N
        • Løgager V
        • 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: 311-319https://doi.org/10.1016/j.euo.2018.09.001
        • Clements MB
        • Vertosick EA
        • Guerrios-Rivera L
        • et al.
        Defining the impact of family history on detection of high-grade prostate cancer in a large multi-institutional cohort.
        Eur Urol. 2021; (Published onlineS0302283821022223)https://doi.org/10.1016/j.eururo.2021.12.011
        • Doan DK
        • Schmidt KT
        • Chau CH
        • Figg WD.
        Germline genetics of prostate cancer: prevalence of risk variants and clinical implications for disease management.
        Cancers. 2021; 13: 2154https://doi.org/10.3390/cancers13092154
        • Tan WS
        • Wong A
        • Mahmalji W
        • Raza A.
        Is there still a role for digital rectal examination in the prostate cancer diagnostic pathway in the COVID-19 and post COVID-19 era?.
        Aging Male. 2021; 24: 92-94https://doi.org/10.1080/13685538.2020.1786047
        • Patel S
        • Douglas-Moore J.
        A reflection on an adapted approach from face-to-face to telephone consultations in our Urology Outpatient Department during the COVID-19 pandemic - a pathway for change to future practice? Changing Urology practice due to COVID-19.
        BJU Int. 2020; 126: 339-341https://doi.org/10.1111/bju.15119
        • Butaney M
        • Rambhatla A.
        The impact of COVID-19 on urology office visits and adoption of telemedicine services.
        Curr Opin Urol. 2022; 32: 152-157https://doi.org/10.1097/MOU.0000000000000957