BioPrev-C - Development and Validation of a Contemporary Prostate Cancer Risk Calculator

Overview

Journal Front Oncol

Specialty Oncology

Date 2024 Mar 7

PMID 38450183

Authors

Thomas Hermanns

Marian S Wettstein

Basil Kaufmann

Noemie Lautenbach

Ernest Kaufmann

Karim Saba

Florian A Schmid

Andreas M Hotker

Michael Muntener

Martin Umbehr

Cedric Poyet

Affiliations

Soon will be listed here.

Abstract

Objectives: To develop a novel biopsy prostate cancer (PCa) prevention calculator (BioPrev-C) using data from a prospective cohort all undergoing mpMRI targeted and transperineal template saturation biopsy.

Materials And Methods: Data of all men who underwent prostate biopsy in our academic tertiary care center between 11/2016 and 10/2019 was prospectively collected. We developed a clinical prediction model for the detection of high-grade PCa (Gleason score ≥7) based on a multivariable logistic regression model incorporating age, PSA, prostate volume, digital rectal examination, family history, previous negative biopsy, 5-alpha-reductase inhibitor use and MRI PI-RADS score. BioPrev-C performance was externally validated in another prospective Swiss cohort and compared with two other PCa risk-calculators (SWOP-RC and PBCG-RC).

Results: Of 391 men in the development cohort, 157 (40.2%) were diagnosed with high-grade PCa. Validation of the BioPrev C revealed good discrimination with an area under the curve for high-grade PCa of 0.88 (95% Confidence Interval 0.82-0.93), which was higher compared to the other two risk calculators (0.71 for PBCG and 0.84 for SWOP). The BioPrev-C revealed good calibration in the low-risk range (0 - 0.25) and moderate overestimation in the intermediate risk range (0.25 - 0.75). The PBCG-RC showed good calibration and the SWOP-RC constant underestimation of high-grade PCa over the whole prediction range. Decision curve analyses revealed a clinical net benefit for the BioPrev-C at a clinical meaningful threshold probability range (≥4%), whereas PBCG and SWOP calculators only showed clinical net benefit above a 30% threshold probability.

Conclusion: BiopPrev-C is a novel contemporary risk calculator for the prediction of high-grade PCa. External validation of the BioPrev-C revealed relevant clinical benefit, which was superior compared to other well-known risk calculators. The BioPrev-C has the potential to significantly and safely reduce the number of men who should undergo a prostate biopsy.

References

Verbeek J, Bangma C, Kweldam C, van der Kwast T, Kummerlin I, van Leenders G . Reducing unnecessary biopsies while detecting clinically significant prostate cancer including cribriform growth with the ERSPC Rotterdam risk calculator and 4Kscore. Urol Oncol. 2018; 37(2):138-144. DOI: 10.1016/j.urolonc.2018.11.021. View

Alberts A, Roobol M, Verbeek J, Schoots I, Chiu P, Osses D . 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. 2018; 75(2):310-318. DOI: 10.1016/j.eururo.2018.07.031. View

van Poppel H, Roobol M, Chapple C, Catto J, Ndow J, Sonksen J . Prostate-specific Antigen Testing as Part of a Risk-Adapted Early Detection Strategy for Prostate Cancer: European Association of Urology Position and Recommendations for 2021. Eur Urol. 2021; 80(6):703-711. DOI: 10.1016/j.eururo.2021.07.024. View

Roobol M, van Vugt H, Loeb S, Zhu X, Bul M, Bangma C . Prediction of prostate cancer risk: the role of prostate volume and digital rectal examination in the ERSPC risk calculators. Eur Urol. 2011; 61(3):577-83. DOI: 10.1016/j.eururo.2011.11.012. View

Cornford P, van den Bergh R, Briers E, Van den Broeck T, Cumberbatch M, De Santis M . EAU-EANM-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer. Part II-2020 Update: Treatment of Relapsing and Metastatic Prostate Cancer. Eur Urol. 2020; 79(2):263-282. DOI: 10.1016/j.eururo.2020.09.046. View

Kundu S, Aulchenko Y, Van Duijn C, Janssens A . PredictABEL: an R package for the assessment of risk prediction models. Eur J Epidemiol. 2011; 26(4):261-4. PMC: 3088798. DOI: 10.1007/s10654-011-9567-4. View

Ankerst D, Boeck A, Freedland S, Stephen Jones J, Cronin A, Roobol M . Evaluating the Prostate Cancer Prevention Trial High Grade Prostate Cancer Risk Calculator in 10 international biopsy cohorts: results from the Prostate Biopsy Collaborative Group. World J Urol. 2012; 32(1):185-91. PMC: 3702682. DOI: 10.1007/s00345-012-0869-2. View

Nordstrom T, Discacciati A, Bergman M, Clements M, Aly M, Annerstedt M . Prostate cancer screening using a combination of risk-prediction, MRI, and targeted prostate biopsies (STHLM3-MRI): a prospective, population-based, randomised, open-label, non-inferiority trial. Lancet Oncol. 2021; 22(9):1240-1249. DOI: 10.1016/S1470-2045(21)00348-X. View

Gentile F, La Civita E, Della Ventura B, Ferro M, Bruzzese D, Crocetto F . A Neural Network Model Combining [-2]proPSA, freePSA, Total PSA, Cathepsin D, and Thrombospondin-1 Showed Increased Accuracy in the Identification of Clinically Significant Prostate Cancer. Cancers (Basel). 2023; 15(5). PMC: 10000171. DOI: 10.3390/cancers15051355. View

10.

Clements M, Vertosick E, Guerrios-Rivera L, De Hoedt A, Hernandez J, Liss M . Defining the Impact of Family History on Detection of High-grade Prostate Cancer in a Large Multi-institutional Cohort. Eur Urol. 2022; 82(2):163-169. PMC: 9243191. DOI: 10.1016/j.eururo.2021.12.011. View

11.

Vickers A, Cronin A, Roobol M, Hugosson J, Stephen Jones J, Kattan M . The relationship between prostate-specific antigen and prostate cancer risk: the Prostate Biopsy Collaborative Group. Clin Cancer Res. 2010; 16(17):4374-81. PMC: 2937360. DOI: 10.1158/1078-0432.CCR-10-1328. View

12.

Cavadas V, Osorio L, Sabell F, Teves F, Branco F, Silva-Ramos M . Prostate cancer prevention trial and European randomized study of screening for prostate cancer risk calculators: a performance comparison in a contemporary screened cohort. Eur Urol. 2010; 58(4):551-8. DOI: 10.1016/j.eururo.2010.06.023. View

13.

Lundon D, Kelly B, Foley R, Loeb S, Fitzpatrick J, Watson R . Prostate cancer risk assessment tools in an unscreened population. World J Urol. 2014; 33(6):827-32. DOI: 10.1007/s00345-014-1365-7. View

14.

Weinreb J, Barentsz J, Choyke P, Cornud F, Haider M, Macura K . PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 2015; 69(1):16-40. PMC: 6467207. DOI: 10.1016/j.eururo.2015.08.052. View

15.

Nam R, Kattan M, Chin J, Trachtenberg J, Singal R, Rendon R . Prospective multi-institutional study evaluating the performance of prostate cancer risk calculators. J Clin Oncol. 2011; 29(22):2959-64. DOI: 10.1200/JCO.2010.32.6371. View

16.

Vickers A, Elkin E . Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006; 26(6):565-74. PMC: 2577036. DOI: 10.1177/0272989X06295361. View

17.

Trottier G, Roobol M, Lawrentschuk N, Bostrom P, Fernandes K, Finelli A . Comparison of risk calculators from the Prostate Cancer Prevention Trial and the European Randomized Study of Screening for Prostate Cancer in a contemporary Canadian cohort. BJU Int. 2011; 108(8 Pt 2):E237-44. DOI: 10.1111/j.1464-410X.2011.10207.x. View

18.

Poyet C, Nieboer D, Bhindi B, Kulkarni G, Wiederkehr C, Wettstein M . Prostate cancer risk prediction using the novel versions of the European Randomised Study for Screening of Prostate Cancer (ERSPC) and Prostate Cancer Prevention Trial (PCPT) risk calculators: independent validation and comparison in a contemporary.... BJU Int. 2015; 117(3):401-8. DOI: 10.1111/bju.13314. View

19.

Kaufmann B, Saba K, Schmidli T, Stutz S, Bissig L, Britschgi A . Prostate cancer detection rate in men undergoing transperineal template-guided saturation and targeted prostate biopsy. Prostate. 2021; 82(3):388-396. PMC: 9299705. DOI: 10.1002/pros.24286. View

20.

Loeb S, Shin S, Broyles D, Wei J, Sanda M, Klee G . Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer. BJU Int. 2016; 120(1):61-68. PMC: 5392379. DOI: 10.1111/bju.13676. View